Bottini, Silvia; Hamouda-Tekaya, Nedra; Tanasa, Bogdan; Zaragosi, Laure-Emmanuelle; Grandjean, Valerie; Repetto, Emanuela; Trabucchi, Michele
2017-05-19
Experimental evidence indicates that about 60% of miRNA-binding activity does not follow the canonical rule about the seed matching between miRNA and target mRNAs, but rather a non-canonical miRNA targeting activity outside the seed or with a seed-like motifs. Here, we propose a new unbiased method to identify canonical and non-canonical miRNA-binding sites from peaks identified by Ago2 Cross-Linked ImmunoPrecipitation associated to high-throughput sequencing (CLIP-seq). Since the quality of peaks is of pivotal importance for the final output of the proposed method, we provide a comprehensive benchmarking of four peak detection programs, namely CIMS, PIPE-CLIP, Piranha and Pyicoclip, on four publicly available Ago2-HITS-CLIP datasets and one unpublished in-house Ago2-dataset in stem cells. We measured the sensitivity, the specificity and the position accuracy toward miRNA binding sites identification, and the agreement with TargetScan. Secondly, we developed a new pipeline, called miRBShunter, to identify canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter was tested and experimentally validated on the in-house Ago2-dataset and on an Ago2-PAR-CLIP dataset in human stem cells. Overall, we provide guidelines to choose a suitable peak detection program and a new method for miRNA-target identification. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.
Directory of Open Access Journals (Sweden)
Emi Sei
2015-02-01
Full Text Available The Kaposi's sarcoma associated herpesvirus (KSHV is an oncogenic virus that causes Kaposi's sarcoma, primary effusion lymphoma (PEL, and some forms of multicentric Castleman's disease. The KSHV ORF57 protein is a conserved posttranscriptional regulator of gene expression that is essential for virus replication. ORF57 is multifunctional, but most of its activities are directly linked to its ability to bind RNA. We globally identified virus and host RNAs bound by ORF57 during lytic reactivation in PEL cells using high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP. As expected, ORF57-bound RNA fragments mapped throughout the KSHV genome, including the known ORF57 ligand PAN RNA. In agreement with previously published ChIP results, we observed that ORF57 bound RNAs near the oriLyt regions of the genome. Examination of the host RNA fragments revealed that a subset of the ORF57-bound RNAs was derived from transcript 5' ends. The position of these 5'-bound fragments correlated closely with the 5'-most exon-intron junction of the pre-mRNA. We selected four candidates (BTG1, EGR1, ZFP36, and TNFSF9 and analyzed their pre-mRNA and mRNA levels during lytic phase. Analysis of both steady-state and newly made RNAs revealed that these candidate ORF57-bound pre-mRNAs persisted for longer periods of time throughout infection than control RNAs, consistent with a role for ORF57 in pre-mRNA metabolism. In addition, exogenous expression of ORF57 was sufficient to increase the pre-mRNA levels and, in one case, the mRNA levels of the putative ORF57 targets. These results demonstrate that ORF57 interacts with specific host pre-mRNAs during lytic reactivation and alters their processing, likely by stabilizing pre-mRNAs. These data suggest that ORF57 is involved in modulating host gene expression in addition to KSHV gene expression during lytic reactivation.
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Hjaltason, Johan
2005-01-01
We analyze the relation between iterative decoding and the extended parity check matrix. By considering a modified version of bit flipping, which produces a list of decoded words, we derive several relations between decodable error patterns and the parameters of the code. By developing a tree...... of codewords at minimal distance from the received vector, we also obtain new information about the code....
Forced Sequence Sequential Decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis
In this thesis we describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon codes with non-uniform profile. With this scheme decoding with good performance...... is possible as low as Eb/No=0.6 dB, which is about 1.7 dB below the signal-to-noise ratio that marks the cut-off rate for the convolutional code. This is possible since the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability...... of computational overflow. Analytical results for the probability that the first Reed-Solomon word is decoded after C computations are presented. This is supported by simulation results that are also extended to other parameters....
DEFF Research Database (Denmark)
Martins, Bo; Forchhammer, Søren
1999-01-01
MPEG-2 video decoding is examined. A unified approach to quality improvement, chrominance upsampling, de-interlacing and superresolution is presented. The information over several frames is combined as part of the processing....
Forced Sequence Sequential Decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis; Paaske, Erik
1998-01-01
We describe a new concatenated decoding scheme based on iterations between an inner sequentially decoded convolutional code of rate R=1/4 and memory M=23, and block interleaved outer Reed-Solomon (RS) codes with nonuniform profile. With this scheme decoding with good performance is possible as low...... as Eb/N0=0.6 dB, which is about 1.25 dB below the signal-to-noise ratio (SNR) that marks the cutoff rate for the full system. Accounting for about 0.45 dB due to the outer codes, sequential decoding takes place at about 1.7 dB below the SNR cutoff rate for the convolutional code. This is possible since...... the iteration process provides the sequential decoders with side information that allows a smaller average load and minimizes the probability of computational overflow. Analytical results for the probability that the first RS word is decoded after C computations are presented. These results are supported...
Decoding communities in networks
Radicchi, Filippo
2018-02-01
According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.
Decoding communities in networks.
Radicchi, Filippo
2018-02-01
According to a recent information-theoretical proposal, the problem of defining and identifying communities in networks can be interpreted as a classical communication task over a noisy channel: memberships of nodes are information bits erased by the channel, edges and nonedges in the network are parity bits introduced by the encoder but degraded through the channel, and a community identification algorithm is a decoder. The interpretation is perfectly equivalent to the one at the basis of well-known statistical inference algorithms for community detection. The only difference in the interpretation is that a noisy channel replaces a stochastic network model. However, the different perspective gives the opportunity to take advantage of the rich set of tools of coding theory to generate novel insights on the problem of community detection. In this paper, we illustrate two main applications of standard coding-theoretical methods to community detection. First, we leverage a state-of-the-art decoding technique to generate a family of quasioptimal community detection algorithms. Second and more important, we show that the Shannon's noisy-channel coding theorem can be invoked to establish a lower bound, here named as decodability bound, for the maximum amount of noise tolerable by an ideal decoder to achieve perfect detection of communities. When computed for well-established synthetic benchmarks, the decodability bound explains accurately the performance achieved by the best community detection algorithms existing on the market, telling us that only little room for their improvement is still potentially left.
Adaptive decoding of convolutional codes
Directory of Open Access Journals (Sweden)
K. Hueske
2007-06-01
Full Text Available Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.
Adaptive decoding of convolutional codes
Hueske, K.; Geldmacher, J.; Götze, J.
2007-06-01
Convolutional codes, which are frequently used as error correction codes in digital transmission systems, are generally decoded using the Viterbi Decoder. On the one hand the Viterbi Decoder is an optimum maximum likelihood decoder, i.e. the most probable transmitted code sequence is obtained. On the other hand the mathematical complexity of the algorithm only depends on the used code, not on the number of transmission errors. To reduce the complexity of the decoding process for good transmission conditions, an alternative syndrome based decoder is presented. The reduction of complexity is realized by two different approaches, the syndrome zero sequence deactivation and the path metric equalization. The two approaches enable an easy adaptation of the decoding complexity for different transmission conditions, which results in a trade-off between decoding complexity and error correction performance.
DEFF Research Database (Denmark)
Nielsen, Rasmus Refslund
2002-01-01
This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed.......This paper describes an efficient decoding method for a recent construction of good linear codes as well as an extension to the construction. Furthermore, asymptotic properties and list decoding of the codes are discussed....
Indian Academy of Sciences (India)
Shannon limit of the channel. Among the earliest discovered codes that approach the. Shannon limit were the low density parity check (LDPC) codes. The term low density arises from the property of the parity check matrix defining the code. We will now define this matrix and the role that it plays in decoding. 2. Linear Codes.
On minimizing the maximum broadcast decoding delay for instantly decodable network coding
Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Ai-Naffouri, Tareq Y.
2014-01-01
In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a
CERN. Geneva. Audiovisual Unit; Antonerakis, S E
2002-01-01
Decoding the Human genome is a very up-to-date topic, raising several questions besides purely scientific, in view of the two competing teams (public and private), the ethics of using the results, and the fact that the project went apparently faster and easier than expected. The lecture series will address the following chapters: Scientific basis and challenges. Ethical and social aspects of genomics.
Decoding Facial Expressions: A New Test with Decoding Norms.
Leathers, Dale G.; Emigh, Ted H.
1980-01-01
Describes the development and testing of a new facial meaning sensitivity test designed to determine how specialized are the meanings that can be decoded from facial expressions. Demonstrates the use of the test to measure a receiver's current level of skill in decoding facial expressions. (JMF)
List Decoding of Algebraic Codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde
We investigate three paradigms for polynomial-time decoding of Reed–Solomon codes beyond half the minimum distance: the Guruswami–Sudan algorithm, Power decoding and the Wu algorithm. The main results concern shaping the computational core of all three methods to a problem solvable by module...... Hermitian codes using Guruswami–Sudan or Power decoding faster than previously known, and we show how to Wu list decode binary Goppa codes....... to solve such using module minimisation, or using our new Demand–Driven algorithm which is also based on module minimisation. The decoding paradigms are all derived and analysed in a self-contained manner, often in new ways or examined in greater depth than previously. Among a number of new results, we...
Bogler, Carsten; Mehnert, Jan; Steinbrink, Jens; Haynes, John-Dylan
2014-01-01
Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS). NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.
Directory of Open Access Journals (Sweden)
Carsten Bogler
Full Text Available Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS. NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.
Astrophysics Decoding the cosmos
Irwin, Judith A
2007-01-01
Astrophysics: Decoding the Cosmos is an accessible introduction to the key principles and theories underlying astrophysics. This text takes a close look at the radiation and particles that we receive from astronomical objects, providing a thorough understanding of what this tells us, drawing the information together using examples to illustrate the process of astrophysics. Chapters dedicated to objects showing complex processes are written in an accessible manner and pull relevant background information together to put the subject firmly into context. The intention of the author is that the book will be a 'tool chest' for undergraduate astronomers wanting to know the how of astrophysics. Students will gain a thorough grasp of the key principles, ensuring that this often-difficult subject becomes more accessible.
Neural Decoder for Topological Codes
Torlai, Giacomo; Melko, Roger G.
2017-07-01
We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning. We provide a general prescription for the training of the network and a decoding strategy that is applicable to a wide variety of stabilizer codes with very little specialization. We demonstrate the neural decoder numerically on the well-known two-dimensional toric code with phase-flip errors.
Fast decoding algorithms for geometric coded apertures
International Nuclear Information System (INIS)
Byard, Kevin
2015-01-01
Fast decoding algorithms are described for the class of coded aperture designs known as geometric coded apertures which were introduced by Gourlay and Stephen. When compared to the direct decoding method, the algorithms significantly reduce the number of calculations required when performing the decoding for these apertures and hence speed up the decoding process. Experimental tests confirm the efficacy of these fast algorithms, demonstrating a speed up of approximately two to three orders of magnitude over direct decoding.
Orientation decoding: Sense in spirals?
Clifford, Colin W G; Mannion, Damien J
2015-04-15
The orientation of a visual stimulus can be successfully decoded from the multivariate pattern of fMRI activity in human visual cortex. Whether this capacity requires coarse-scale orientation biases is controversial. We and others have advocated the use of spiral stimuli to eliminate a potential coarse-scale bias-the radial bias toward local orientations that are collinear with the centre of gaze-and hence narrow down the potential coarse-scale biases that could contribute to orientation decoding. The usefulness of this strategy is challenged by the computational simulations of Carlson (2014), who reported the ability to successfully decode spirals of opposite sense (opening clockwise or counter-clockwise) from the pooled output of purportedly unbiased orientation filters. Here, we elaborate the mathematical relationship between spirals of opposite sense to confirm that they cannot be discriminated on the basis of the pooled output of unbiased or radially biased orientation filters. We then demonstrate that Carlson's (2014) reported decoding ability is consistent with the presence of inadvertent biases in the set of orientation filters; biases introduced by their digital implementation and unrelated to the brain's processing of orientation. These analyses demonstrate that spirals must be processed with an orientation bias other than the radial bias for successful decoding of spiral sense. Copyright © 2014 Elsevier Inc. All rights reserved.
Improved decoding for a concatenated coding system
DEFF Research Database (Denmark)
Paaske, Erik
1990-01-01
The concatenated coding system recommended by CCSDS (Consultative Committee for Space Data Systems) uses an outer (255,233) Reed-Solomon (RS) code based on 8-b symbols, followed by the block interleaver and an inner rate 1/2 convolutional code with memory 6. Viterbi decoding is assumed. Two new...... decoding procedures based on repeated decoding trials and exchange of information between the two decoders and the deinterleaver are proposed. In the first one, where the improvement is 0.3-0.4 dB, only the RS decoder performs repeated trials. In the second one, where the improvement is 0.5-0.6 dB, both...... decoders perform repeated decoding trials and decoding information is exchanged between them...
Soft-decision decoding of RS codes
DEFF Research Database (Denmark)
Justesen, Jørn
2005-01-01
By introducing a few simplifying assumptions we derive a simple condition for successful decoding using the Koetter-Vardy algorithm for soft-decision decoding of RS codes. We show that the algorithm has a significant advantage over hard decision decoding when the code rate is low, when two or more...
Toric Codes, Multiplicative Structure and Decoding
DEFF Research Database (Denmark)
Hansen, Johan Peder
2017-01-01
Long linear codes constructed from toric varieties over finite fields, their multiplicative structure and decoding. The main theme is the inherent multiplicative structure on toric codes. The multiplicative structure allows for \\emph{decoding}, resembling the decoding of Reed-Solomon codes and al...
FPGA Realization of Memory 10 Viterbi Decoder
DEFF Research Database (Denmark)
Paaske, Erik; Bach, Thomas Bo; Andersen, Jakob Dahl
1997-01-01
sequence mode when feedback from the Reed-Solomon decoder is available. The Viterbi decoder is realized using two Altera FLEX 10K50 FPGA's. The overall operating speed is 30 kbit/s, and since up to three iterations are performed for each frame and only one decoder is used, the operating speed...
Decoding intention at sensorimotor timescales.
Directory of Open Access Journals (Sweden)
Mathew Salvaris
Full Text Available The ability to decode an individual's intentions in real time has long been a 'holy grail' of research on human volition. For example, a reliable method could be used to improve scientific study of voluntary action by allowing external probe stimuli to be delivered at different moments during development of intention and action. Several Brain Computer Interface applications have used motor imagery of repetitive actions to achieve this goal. These systems are relatively successful, but only if the intention is sustained over a period of several seconds; much longer than the timescales identified in psychophysiological studies for normal preparation for voluntary action. We have used a combination of sensorimotor rhythms and motor imagery training to decode intentions in a single-trial cued-response paradigm similar to those used in human and non-human primate motor control research. Decoding accuracy of over 0.83 was achieved with twelve participants. With this approach, we could decode intentions to move the left or right hand at sub-second timescales, both for instructed choices instructed by an external stimulus and for free choices generated intentionally by the participant. The implications for volition are considered.
Dynamics of intracellular information decoding
International Nuclear Information System (INIS)
Kobayashi, Tetsuya J; Kamimura, Atsushi
2011-01-01
A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity
Dynamics of intracellular information decoding.
Kobayashi, Tetsuya J; Kamimura, Atsushi
2011-10-01
A variety of cellular functions are robust even to substantial intrinsic and extrinsic noise in intracellular reactions and the environment that could be strong enough to impair or limit them. In particular, of substantial importance is cellular decision-making in which a cell chooses a fate or behavior on the basis of information conveyed in noisy external signals. For robust decoding, the crucial step is filtering out the noise inevitably added during information transmission. As a minimal and optimal implementation of such an information decoding process, the autocatalytic phosphorylation and autocatalytic dephosphorylation (aPadP) cycle was recently proposed. Here, we analyze the dynamical properties of the aPadP cycle in detail. We describe the dynamical roles of the stationary and short-term responses in determining the efficiency of information decoding and clarify the optimality of the threshold value of the stationary response and its information-theoretical meaning. Furthermore, we investigate the robustness of the aPadP cycle against the receptor inactivation time and intrinsic noise. Finally, we discuss the relationship among information decoding with information-dependent actions, bet-hedging and network modularity.
Human Genome Research: Decoding DNA
dropdown arrow Site Map A-Z Index Menu Synopsis Human Genome Research: Decoding DNA Resources with of the DNA double helix during April 2003. James D. Watson, Francis Crick, and Maurice Wilkins were company Celera announced the completion of a "working draft" reference DNA sequence of the human
Liu, K. Y.
1986-01-01
High-speed decoder intended for use with Reed-Solomon (RS) codes of long code length and high error-correcting capability. Design based on algorithm that includes high-radix Fermat transform procedure, which is most efficient for high speeds. RS code in question has code-word length of 256 symbols, of which 224 are information symbols and 32 are redundant.
On Decoding Interleaved Chinese Remainder Codes
DEFF Research Database (Denmark)
Li, Wenhui; Sidorenko, Vladimir; Nielsen, Johan Sebastian Rosenkilde
2013-01-01
We model the decoding of Interleaved Chinese Remainder codes as that of finding a short vector in a Z-lattice. Using the LLL algorithm, we obtain an efficient decoding algorithm, correcting errors beyond the unique decoding bound and having nearly linear complexity. The algorithm can fail...... with a probability dependent on the number of errors, and we give an upper bound for this. Simulation results indicate that the bound is close to the truth. We apply the proposed decoding algorithm for decoding a single CR code using the idea of “Power” decoding, suggested for Reed-Solomon codes. A combination...... of these two methods can be used to decode low-rate Interleaved Chinese Remainder codes....
LDPC Decoding on GPU for Mobile Device
Directory of Open Access Journals (Sweden)
Yiqin Lu
2016-01-01
Full Text Available A flexible software LDPC decoder that exploits data parallelism for simultaneous multicode words decoding on the mobile device is proposed in this paper, supported by multithreading on OpenCL based graphics processing units. By dividing the check matrix into several parts to make full use of both the local memory and private memory on GPU and properly modify the code capacity each time, our implementation on a mobile phone shows throughputs above 100 Mbps and delay is less than 1.6 millisecond in decoding, which make high-speed communication like video calling possible. To realize efficient software LDPC decoding on the mobile device, the LDPC decoding feature on communication baseband chip should be replaced to save the cost and make it easier to upgrade decoder to be compatible with a variety of channel access schemes.
A class of Sudan-decodable codes
DEFF Research Database (Denmark)
Nielsen, Rasmus Refslund
2000-01-01
In this article, Sudan's algorithm is modified into an efficient method to list-decode a class of codes which can be seen as a generalization of Reed-Solomon codes. The algorithm is specialized into a very efficient method for unique decoding. The code construction can be generalized based...... on algebraic-geometry codes and the decoding algorithms are generalized accordingly. Comparisons with Reed-Solomon and Hermitian codes are made....
Interior point decoding for linear vector channels
International Nuclear Information System (INIS)
Wadayama, T
2008-01-01
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem
Interior point decoding for linear vector channels
Energy Technology Data Exchange (ETDEWEB)
Wadayama, T [Nagoya Institute of Technology, Gokiso, Showa-ku, Nagoya, Aichi, 466-8555 (Japan)], E-mail: wadayama@nitech.ac.jp
2008-01-15
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter-symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem.
Video encoder/decoder for encoding/decoding motion compensated images
1996-01-01
Video encoder and decoder, provided with a motion compensator for motion-compensated video coding or decoding in which a picture is coded or decoded in blocks in alternately horizontal and vertical steps. The motion compensator is provided with addressing means (160) and controlled multiplexers
Evaluation framework for K-best sphere decoders
Shen, Chungan; Eltawil, Ahmed M.; Salama, Khaled N.
2010-01-01
or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature
Concatenated coding system with iterated sequential inner decoding
DEFF Research Database (Denmark)
Jensen, Ole Riis; Paaske, Erik
1995-01-01
We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder......We describe a concatenated coding system with iterated sequential inner decoding. The system uses convolutional codes of very long constraint length and operates on iterations between an inner Fano decoder and an outer Reed-Solomon decoder...
Application of Beyond Bound Decoding for High Speed Optical Communications
DEFF Research Database (Denmark)
Li, Bomin; Larsen, Knud J.; Vegas Olmos, Juan José
2013-01-01
This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB.......This paper studies the application of beyond bound decoding method for high speed optical communications. This hard-decision decoding method outperforms traditional minimum distance decoding method, with a total net coding gain of 10.36 dB....
On minimizing the maximum broadcast decoding delay for instantly decodable network coding
Douik, Ahmed S.
2014-09-01
In this paper, we consider the problem of minimizing the maximum broadcast decoding delay experienced by all the receivers of generalized instantly decodable network coding (IDNC). Unlike the sum decoding delay, the maximum decoding delay as a definition of delay for IDNC allows a more equitable distribution of the delays between the different receivers and thus a better Quality of Service (QoS). In order to solve this problem, we first derive the expressions for the probability distributions of maximum decoding delay increments. Given these expressions, we formulate the problem as a maximum weight clique problem in the IDNC graph. Although this problem is known to be NP-hard, we design a greedy algorithm to perform effective packet selection. Through extensive simulations, we compare the sum decoding delay and the max decoding delay experienced when applying the policies to minimize the sum decoding delay and our policy to reduce the max decoding delay. Simulations results show that our policy gives a good agreement among all the delay aspects in all situations and outperforms the sum decoding delay policy to effectively minimize the sum decoding delay when the channel conditions become harsher. They also show that our definition of delay significantly improve the number of served receivers when they are subject to strict delay constraints.
Best linear decoding of random mask images
International Nuclear Information System (INIS)
Woods, J.W.; Ekstrom, M.P.; Palmieri, T.M.; Twogood, R.E.
1975-01-01
In 1968 Dicke proposed coded imaging of x and γ rays via random pinholes. Since then, many authors have agreed with him that this technique can offer significant image improvement. A best linear decoding of the coded image is presented, and its superiority over the conventional matched filter decoding is shown. Experimental results in the visible light region are presented. (U.S.)
Oppositional Decoding as an Act of Resistance.
Steiner, Linda
1988-01-01
Argues that contributors to the "No Comment" feature of "Ms." magazine are engaging in oppositional decoding and speculates on why this is a satisfying group process. Also notes such decoding presents another challenge to the idea that mass media has the same effect on all audiences. (SD)
High Speed Frame Synchronization and Viterbi Decoding
DEFF Research Database (Denmark)
Paaske, Erik; Justesen, Jørn; Larsen, Knud J.
1996-01-01
The purpose of Phase 1 of the study is to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. The systems we consider are high data rate space communication systems. Also...... components. Node synchronization performed within a Viterbi decoder is discussed, and algorithms for frame synchronization are described and analyzed. We present a list of system configurations that we find potentially useful. Further, the high level architecture of units that contain frame synchronization...... and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder and another for placement after the decoder. The high level architectures of three possible implementations of Viterbi decoders are described: The first...
High Speed Frame Synchronization and Viterbi Decoding
DEFF Research Database (Denmark)
Paaske, Erik; Justesen, Jørn; Larsen, Knud J.
1998-01-01
The study has been divided into two phases. The purpose of Phase 1 of the study was to describe the system structure and algorithms in sufficient detail to allow drawing the high level architecture of units containing frame synchronization and Viterbi decoding. After selection of which specific...... potentially useful.Algorithms for frame synchronization are described and analyzed. Further, the high level architecture of units that contain frame synchronization and various other functions needed in a complete system is presented. Two such units are described, one for placement before the Viterbi decoder...... towards a realization in an FPGA.Node synchronization performed within a Viterbi decoder is discussed, and the high level architectures of three possible implementations of Viterbi decoders are described: The first implementation uses a number of commercially available decoders while the the two others...
Fast decoders for qudit topological codes
International Nuclear Information System (INIS)
Anwar, Hussain; Brown, Benjamin J; Campbell, Earl T; Browne, Dan E
2014-01-01
Qudit toric codes are a natural higher-dimensional generalization of the well-studied qubit toric code. However, standard methods for error correction of the qubit toric code are not applicable to them. Novel decoders are needed. In this paper we introduce two renormalization group decoders for qudit codes and analyse their error correction thresholds and efficiency. The first decoder is a generalization of a ‘hard-decisions’ decoder due to Bravyi and Haah (arXiv:1112.3252). We modify this decoder to overcome a percolation effect which limits its threshold performance for many-level quantum systems. The second decoder is a generalization of a ‘soft-decisions’ decoder due to Poulin and Duclos-Cianci (2010 Phys. Rev. Lett. 104 050504), with a small cell size to optimize the efficiency of implementation in the high dimensional case. In each case, we estimate thresholds for the uncorrelated bit-flip error model and provide a comparative analysis of the performance of both these approaches to error correction of qudit toric codes. (paper)
Iterative Decoding of Concatenated Codes: A Tutorial
Directory of Open Access Journals (Sweden)
Phillip A. Regalia
2005-05-01
Full Text Available The turbo decoding algorithm of a decade ago constituted a milestone in error-correction coding for digital communications, and has inspired extensions to generalized receiver topologies, including turbo equalization, turbo synchronization, and turbo CDMA, among others. Despite an accrued understanding of iterative decoding over the years, the Ã¢Â€Âœturbo principleÃ¢Â€Â remains elusive to master analytically, thereby inciting interest from researchers outside the communications domain. In this spirit, we develop a tutorial presentation of iterative decoding for parallel and serial concatenated codes, in terms hopefully accessible to a broader audience. We motivate iterative decoding as a computationally tractable attempt to approach maximum-likelihood decoding, and characterize fixed points in terms of a Ã¢Â€ÂœconsensusÃ¢Â€Â property between constituent decoders. We review how the decoding algorithm for both parallel and serial concatenated codes coincides with an alternating projection algorithm, which allows one to identify conditions under which the algorithm indeed converges to a maximum-likelihood solution, in terms of particular likelihood functions factoring into the product of their marginals. The presentation emphasizes a common framework applicable to both parallel and serial concatenated codes.
Decoding small surface codes with feedforward neural networks
Varsamopoulos, Savvas; Criger, Ben; Bertels, Koen
2018-01-01
Surface codes reach high error thresholds when decoded with known algorithms, but the decoding time will likely exceed the available time budget, especially for near-term implementations. To decrease the decoding time, we reduce the decoding problem to a classification problem that a feedforward neural network can solve. We investigate quantum error correction and fault tolerance at small code distances using neural network-based decoders, demonstrating that the neural network can generalize to inputs that were not provided during training and that they can reach similar or better decoding performance compared to previous algorithms. We conclude by discussing the time required by a feedforward neural network decoder in hardware.
The serial message-passing schedule for LDPC decoding algorithms
Liu, Mingshan; Liu, Shanshan; Zhou, Yuan; Jiang, Xue
2015-12-01
The conventional message-passing schedule for LDPC decoding algorithms is the so-called flooding schedule. It has the disadvantage that the updated messages cannot be used until next iteration, thus reducing the convergence speed . In this case, the Layered Decoding algorithm (LBP) based on serial message-passing schedule is proposed. In this paper the decoding principle of LBP algorithm is briefly introduced, and then proposed its two improved algorithms, the grouped serial decoding algorithm (Grouped LBP) and the semi-serial decoding algorithm .They can improve LBP algorithm's decoding speed while maintaining a good decoding performance.
Fast decoding algorithms for coded aperture systems
International Nuclear Information System (INIS)
Byard, Kevin
2014-01-01
Fast decoding algorithms are described for a number of established coded aperture systems. The fast decoding algorithms for all these systems offer significant reductions in the number of calculations required when reconstructing images formed by a coded aperture system and hence require less computation time to produce the images. The algorithms may therefore be of use in applications that require fast image reconstruction, such as near real-time nuclear medicine and location of hazardous radioactive spillage. Experimental tests confirm the efficacy of the fast decoding techniques
Decoding Algorithms for Random Linear Network Codes
DEFF Research Database (Denmark)
Heide, Janus; Pedersen, Morten Videbæk; Fitzek, Frank
2011-01-01
We consider the problem of efficient decoding of a random linear code over a finite field. In particular we are interested in the case where the code is random, relatively sparse, and use the binary finite field as an example. The goal is to decode the data using fewer operations to potentially...... achieve a high coding throughput, and reduce energy consumption.We use an on-the-fly version of the Gauss-Jordan algorithm as a baseline, and provide several simple improvements to reduce the number of operations needed to perform decoding. Our tests show that the improvements can reduce the number...
Three phase full wave dc motor decoder
Studer, P. A. (Inventor)
1977-01-01
A three phase decoder for dc motors is disclosed which employs an extremely simple six transistor circuit to derive six properly phased output signals for fullwave operation of dc motors. Six decoding transistors are coupled at their base-emitter junctions across a resistor network arranged in a delta configuration. Each point of the delta configuration is coupled to one of three position sensors which sense the rotational position of the motor. A second embodiment of the invention is disclosed in which photo-optical isolators are used in place of the decoding transistors.
Improved Power Decoding of One-Point Hermitian Codes
DEFF Research Database (Denmark)
Puchinger, Sven; Bouw, Irene; Rosenkilde, Johan Sebastian Heesemann
2017-01-01
We propose a new partial decoding algorithm for one-point Hermitian codes that can decode up to the same number of errors as the Guruswami–Sudan decoder. Simulations suggest that it has a similar failure probability as the latter one. The algorithm is based on a recent generalization of the power...... decoding algorithm for Reed–Solomon codes and does not require an expensive root-finding step. In addition, it promises improvements for decoding interleaved Hermitian codes....
Decoding of interleaved Reed-Solomon codes using improved power decoding
DEFF Research Database (Denmark)
Puchinger, Sven; Rosenkilde ne Nielsen, Johan
2017-01-01
We propose a new partial decoding algorithm for m-interleaved Reed-Solomon (IRS) codes that can decode, with high probability, a random error of relative weight 1 − Rm/m+1 at all code rates R, in time polynomial in the code length n. For m > 2, this is an asymptotic improvement over the previous...... state-of-the-art for all rates, and the first improvement for R > 1/3 in the last 20 years. The method combines collaborative decoding of IRS codes with power decoding up to the Johnson radius....
Low-Power Bitstream-Residual Decoder for H.264/AVC Baseline Profile Decoding
Directory of Open Access Journals (Sweden)
Xu Ke
2009-01-01
Full Text Available Abstract We present the design and VLSI implementation of a novel low-power bitstream-residual decoder for H.264/AVC baseline profile. It comprises a syntax parser, a parameter decoder, and an Inverse Quantization Inverse Transform (IQIT decoder. The syntax parser detects and decodes each incoming codeword in the bitstream under the control of a hierarchical Finite State Machine (FSM; the IQIT decoder performs inverse transform and quantization with pipelining and parallelism. Various power reduction techniques, such as data-driven based on statistic results, nonuniform partition, precomputation, guarded evaluation, hierarchical FSM decomposition, TAG method, zero-block skipping, and clock gating , are adopted and integrated throughout the bitstream-residual decoder. With innovative architecture, the proposed design is able to decode QCIF video sequences of 30 fps at a clock rate as low as 1.5 MHz. A prototype H.264/AVC baseline decoding chip utilizing the proposed decoder is fabricated in UMC 0.18 m 1P6M CMOS technology. The proposed design is measured under 1 V 1.8 V supply with 0.1 V step. It dissipates 76 W at 1 V and 253 W at 1.8 V.
Decoding Dyslexia, a Common Learning Disability
... if they continue to struggle. Read More "Dyslexic" Articles In Their Own Words: Dealing with Dyslexia / Decoding Dyslexia, a Common Learning Disability / What is Dyslexia? / Special Education and Research ...
Multiuser Random Coding Techniques for Mismatched Decoding
Scarlett, Jonathan; Martinez, Alfonso; Guillén i Fàbregas, Albert
2016-01-01
This paper studies multiuser random coding techniques for channel coding with a given (possibly suboptimal) decoding rule. For the mismatched discrete memoryless multiple-access channel, an error exponent is obtained that is tight with respect to the ensemble average, and positive within the interior of Lapidoth's achievable rate region. This exponent proves the ensemble tightness of the exponent of Liu and Hughes in the case of maximum-likelihood decoding. An equivalent dual form of Lapidoth...
A novel parallel pipeline structure of VP9 decoder
Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan
2018-04-01
To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.
Coding and decoding with dendrites.
Papoutsi, Athanasia; Kastellakis, George; Psarrou, Maria; Anastasakis, Stelios; Poirazi, Panayiota
2014-02-01
Since the discovery of complex, voltage dependent mechanisms in the dendrites of multiple neuron types, great effort has been devoted in search of a direct link between dendritic properties and specific neuronal functions. Over the last few years, new experimental techniques have allowed the visualization and probing of dendritic anatomy, plasticity and integrative schemes with unprecedented detail. This vast amount of information has caused a paradigm shift in the study of memory, one of the most important pursuits in Neuroscience, and calls for the development of novel theories and models that will unify the available data according to some basic principles. Traditional models of memory considered neural cells as the fundamental processing units in the brain. Recent studies however are proposing new theories in which memory is not only formed by modifying the synaptic connections between neurons, but also by modifications of intrinsic and anatomical dendritic properties as well as fine tuning of the wiring diagram. In this review paper we present previous studies along with recent findings from our group that support a key role of dendrites in information processing, including the encoding and decoding of new memories, both at the single cell and the network level. Copyright © 2013 Elsevier Ltd. All rights reserved.
FPGA implementation of low complexity LDPC iterative decoder
Verma, Shivani; Sharma, Sanjay
2016-07-01
Low-density parity-check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min-sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade-off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade-off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate-1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan-3A DSP family.
Performance breakdown in optimal stimulus decoding.
Lubomir Kostal; Lansky, Petr; Pilarski, Stevan
2015-06-01
One of the primary goals of neuroscience is to understand how neurons encode and process information about their environment. The problem is often approached indirectly by examining the degree to which the neuronal response reflects the stimulus feature of interest. In this context, the methods of signal estimation and detection theory provide the theoretical limits on the decoding accuracy with which the stimulus can be identified. The Cramér-Rao lower bound on the decoding precision is widely used, since it can be evaluated easily once the mathematical model of the stimulus-response relationship is determined. However, little is known about the behavior of different decoding schemes with respect to the bound if the neuronal population size is limited. We show that under broad conditions the optimal decoding displays a threshold-like shift in performance in dependence on the population size. The onset of the threshold determines a critical range where a small increment in size, signal-to-noise ratio or observation time yields a dramatic gain in the decoding precision. We demonstrate the existence of such threshold regions in early auditory and olfactory information coding. We discuss the origin of the threshold effect and its impact on the design of effective coding approaches in terms of relevant population size.
Symbol synchronization for the TDRSS decoder
Costello, D. J., Jr.
1983-01-01
Each 8 bits out of the Viterbi decoder correspond to one symbol of the R/S code. Synchronization must be maintained here so that each 8-bit symbol delivered to the R/S decoder corresponds to an 8-bit symbol from the R/S encoder. Lack of synchronization, would cause an error in almost every R/S symbol since even a - 1-bit sync slip shifts every bit in each 8-bit symbol by one position, therby confusing the mapping betweeen 8-bit sequences and symbols. The error correcting capability of the R/S code would be exceeded. Possible ways to correcting this condition include: (1) designing the R/S decoder to recognize the overload and shifting the output sequence of the inner decoder to establish a different sync state; (2) using the characteristics of the inner decoder to establish symbol synchronization for the outer code, with or without a deinterleaver and an interleaver; and (3) modifying the encoder to alternate periodically between two sets of generators.
Modified Decoding Algorithm of LLR-SPA
Directory of Open Access Journals (Sweden)
Zhongxun Wang
2014-09-01
Full Text Available In wireless sensor networks, the energy consumption is mainly occurred in the stage of information transmission. The Low Density Parity Check code can make full use of the channel information to save energy. Because of the widely used decoding algorithm of the Low Density Parity Check code, this paper proposes a new decoding algorithm which is based on the LLR-SPA (Sum-Product Algorithm in Log-Likelihood-domain to improve the accuracy of the decoding algorithm. In the modified algorithm, a piecewise linear function is used to approximate the complicated Jacobi correction term in LLR-SPA decoding algorithm. Construct the tangent by the tangency point to the function of Jacobi correction term, which is based on the first order Taylor Series. In this way, the proposed piecewise linear approximation offers almost a perfect match to the function of Jacobi correction term. Meanwhile, the proposed piecewise linear approximation could avoid the operation of logarithmic which is more suitable for practical application. The simulation results show that the proposed algorithm could improve the decoding accuracy greatly without noticeable variation of the computational complexity.
Completion time reduction in instantly decodable network coding through decoding delay control
Douik, Ahmed S.
2014-12-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users\\' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.
Completion time reduction in instantly decodable network coding through decoding delay control
Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.
2014-01-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to completely act against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. In this paper, we study the effect of controlling the decoding delay to reduce the completion time below its currently best known solution. We first derive the decoding-delay-dependent expressions of the users' and their overall completion times. Although using such expressions to find the optimal overall completion time is NP-hard, we use a heuristic that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Simulation results show that this new algorithm achieves both a lower mean completion time and mean decoding delay compared to the best known heuristic for completion time reduction. The gap in performance becomes significant for harsh erasure scenarios.
NP-hardness of decoding quantum error-correction codes
Hsieh, Min-Hsiu; Le Gall, François
2011-05-01
Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.
NP-hardness of decoding quantum error-correction codes
International Nuclear Information System (INIS)
Hsieh, Min-Hsiu; Le Gall, Francois
2011-01-01
Although the theory of quantum error correction is intimately related to classical coding theory and, in particular, one can construct quantum error-correction codes (QECCs) from classical codes with the dual-containing property, this does not necessarily imply that the computational complexity of decoding QECCs is the same as their classical counterparts. Instead, decoding QECCs can be very much different from decoding classical codes due to the degeneracy property. Intuitively, one expects degeneracy would simplify the decoding since two different errors might not and need not be distinguished in order to correct them. However, we show that general quantum decoding problem is NP-hard regardless of the quantum codes being degenerate or nondegenerate. This finding implies that no considerably fast decoding algorithm exists for the general quantum decoding problems and suggests the existence of a quantum cryptosystem based on the hardness of decoding QECCs.
Generalized Sudan's List Decoding for Order Domain Codes
DEFF Research Database (Denmark)
Geil, Hans Olav; Matsumoto, Ryutaroh
2007-01-01
We generalize Sudan's list decoding algorithm without multiplicity to evaluation codes coming from arbitrary order domains. The number of correctable errors by the proposed method is larger than the original list decoding without multiplicity....
Partially blind instantly decodable network codes for lossy feedback environment
Sorour, Sameh; Douik, Ahmed S.; Valaee, Shahrokh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2014-01-01
an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to find the optimal policy that reduces the decoding delay in such lossy feedback environment. Results show that our proposed solutions both
Neuroprosthetic Decoder Training as Imitation Learning.
Merel, Josh; Carlson, David; Paninski, Liam; Cunningham, John P
2016-05-01
Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger), can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy) for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.
Neuroprosthetic Decoder Training as Imitation Learning.
Directory of Open Access Journals (Sweden)
Josh Merel
2016-05-01
Full Text Available Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In practice, the decoder is often learned by updating its parameters while the user performs a task. When the user's intention is not directly observable, recent methods have demonstrated value in training the decoder against a surrogate for the user's intended movement. Here we show that training a decoder in this way is a novel variant of an imitation learning problem, where an oracle or expert is employed for supervised training in lieu of direct observations, which are not available. Specifically, we describe how a generic imitation learning meta-algorithm, dataset aggregation (DAgger, can be adapted to train a generic brain-computer interface. By deriving existing learning algorithms for brain-computer interfaces in this framework, we provide a novel analysis of regret (an important metric of learning efficacy for brain-computer interfaces. This analysis allows us to characterize the space of algorithmic variants and bounds on their regret rates. Existing approaches for decoder learning have been performed in the cursor control setting, but the available design principles for these decoders are such that it has been impossible to scale them to naturalistic settings. Leveraging our findings, we then offer an algorithm that combines imitation learning with optimal control, which should allow for training of arbitrary effectors for which optimal control can generate goal-oriented control. We demonstrate this novel and general BCI algorithm with simulated neuroprosthetic control of a 26 degree-of-freedom model of an arm, a sophisticated and realistic end effector.
Decoding of concatenated codes with interleaved outer codes
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Thommesen, Christian
2004-01-01
Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes.......Recently Bleichenbacher et al. proposed a decoding algorithm for interleaved (N, K) Reed-Solomon codes, which allows close to N-K errors to be corrected in many cases. We discuss the application of this decoding algorithm to concatenated codes....
Binary Systematic Network Coding for Progressive Packet Decoding
Jones, Andrew L.; Chatzigeorgiou, Ioannis; Tassi, Andrea
2015-01-01
We consider binary systematic network codes and investigate their capability of decoding a source message either in full or in part. We carry out a probability analysis, derive closed-form expressions for the decoding probability and show that systematic network coding outperforms conventional net- work coding. We also develop an algorithm based on Gaussian elimination that allows progressive decoding of source packets. Simulation results show that the proposed decoding algorithm can achieve ...
Decoding Hermitian Codes with Sudan's Algorithm
DEFF Research Database (Denmark)
Høholdt, Tom; Nielsen, Rasmus Refslund
1999-01-01
We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q-polynomial, and a reduct......We present an efficient implementation of Sudan's algorithm for list decoding Hermitian codes beyond half the minimum distance. The main ingredients are an explicit method to calculate so-called increasing zero bases, an efficient interpolation algorithm for finding the Q...
Decoding Interleaved Gabidulin Codes using Alekhnovich's Algorithm
DEFF Research Database (Denmark)
Puchinger, Sven; Müelich, Sven; Mödinger, David
2017-01-01
We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ3n(ω+1)/2log(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is the matrix multiplication exponent.......We prove that Alekhnovich's algorithm can be used for row reduction of skew polynomial matrices. This yields an O(ℓ3n(ω+1)/2log(n)) decoding algorithm for ℓ-Interleaved Gabidulin codes of length n, where ω is the matrix multiplication exponent....
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Kashyap Manohar
2008-01-01
Full Text Available Abstract This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Decoding LDPC Convolutional Codes on Markov Channels
Directory of Open Access Journals (Sweden)
Chris Winstead
2008-04-01
Full Text Available This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.
Decoding algorithm for vortex communications receiver
Kupferman, Judy; Arnon, Shlomi
2018-01-01
Vortex light beams can provide a tremendous alphabet for encoding information. We derive a symbol decoding algorithm for a direct detection matrix detector vortex beam receiver using Laguerre Gauss (LG) modes, and develop a mathematical model of symbol error rate (SER) for this receiver. We compare SER as a function of signal to noise ratio (SNR) for our algorithm and for the Pearson correlation algorithm. To our knowledge, this is the first comprehensive treatment of a decoding algorithm of a matrix detector for an LG receiver.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid; Alouini, Mohamed-Slim
2013-01-01
channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement
Image transmission system using adaptive joint source and channel decoding
Liu, Weiliang; Daut, David G.
2005-03-01
In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.
Decoding and Encoding Facial Expressions in Preschool-Age Children.
Zuckerman, Miron; Przewuzman, Sylvia J.
1979-01-01
Preschool-age children drew, decoded, and encoded facial expressions depicting five different emotions. Accuracy of drawing, decoding and encoding each of the five emotions was consistent across the three tasks; decoding ability was correlated with drawing ability among female subjects, but neither of these abilities was correlated with encoding…
On Rational Interpolation-Based List-Decoding and List-Decoding Binary Goppa Codes
DEFF Research Database (Denmark)
Beelen, Peter; Høholdt, Tom; Nielsen, Johan Sebastian Rosenkilde
2013-01-01
We derive the Wu list-decoding algorithm for generalized Reed–Solomon (GRS) codes by using Gröbner bases over modules and the Euclidean algorithm as the initial algorithm instead of the Berlekamp–Massey algorithm. We present a novel method for constructing the interpolation polynomial fast. We gi...... and a duality in the choice of parameters needed for decoding, both in the case of GRS codes and in the case of Goppa codes....
Bayesian population decoding of spiking neurons.
Gerwinn, Sebastian; Macke, Jakob; Bethge, Matthias
2009-01-01
The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a 'spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.
Faster 2-regular information-set decoding
Bernstein, D.J.; Lange, T.; Peters, C.P.; Schwabe, P.; Chee, Y.M.
2011-01-01
Fix positive integers B and w. Let C be a linear code over F 2 of length Bw. The 2-regular-decoding problem is to find a nonzero codeword consisting of w length-B blocks, each of which has Hamming weight 0 or 2. This problem appears in attacks on the FSB (fast syndrome-based) hash function and
Bayesian population decoding of spiking neurons
Directory of Open Access Journals (Sweden)
Sebastian Gerwinn
2009-10-01
Full Text Available The timing of action potentials in spiking neurons depends on the temporal dynamics of their inputs and contains information about temporal fluctuations in the stimulus. Leaky integrate-and-fire neurons constitute a popular class of encoding models, in which spike times depend directly on the temporal structure of the inputs. However, optimal decoding rules for these models have only been studied explicitly in the noiseless case. Here, we study decoding rules for probabilistic inference of a continuous stimulus from the spike times of a population of leaky integrate-and-fire neurons with threshold noise. We derive three algorithms for approximating the posterior distribution over stimuli as a function of the observed spike trains. In addition to a reconstruction of the stimulus we thus obtain an estimate of the uncertainty as well. Furthermore, we derive a `spike-by-spike' online decoding scheme that recursively updates the posterior with the arrival of each new spike. We use these decoding rules to reconstruct time-varying stimuli represented by a Gaussian process from spike trains of single neurons as well as neural populations.
Sequential decoders for large MIMO systems
Ali, Konpal S.; Abediseid, Walid; Alouini, Mohamed-Slim
2014-01-01
the Sequential Decoder using the Fano Algorithm for large MIMO systems. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity
2010-10-01
..., satellite, public switched telephone network, or any other source that uses the EAS protocol. (2) Valid..., analog radio and television broadcast stations, analog cable systems and wireless cable systems may... program data must be retained even with power removed. (7) Outputs. Decoders shall have the following...
Older Adults Have Difficulty in Decoding Sarcasm
Phillips, Louise H.; Allen, Roy; Bull, Rebecca; Hering, Alexandra; Kliegel, Matthias; Channon, Shelley
2015-01-01
Younger and older adults differ in performance on a range of social-cognitive skills, with older adults having difficulties in decoding nonverbal cues to emotion and intentions. Such skills are likely to be important when deciding whether someone is being sarcastic. In the current study we investigated in a life span sample whether there are…
Bounded-Angle Iterative Decoding of LDPC Codes
Dolinar, Samuel; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush
2009-01-01
Bounded-angle iterative decoding is a modified version of conventional iterative decoding, conceived as a means of reducing undetected-error rates for short low-density parity-check (LDPC) codes. For a given code, bounded-angle iterative decoding can be implemented by means of a simple modification of the decoder algorithm, without redesigning the code. Bounded-angle iterative decoding is based on a representation of received words and code words as vectors in an n-dimensional Euclidean space (where n is an integer).
A Scalable Architecture of a Structured LDPC Decoder
Lee, Jason Kwok-San; Lee, Benjamin; Thorpe, Jeremy; Andrews, Kenneth; Dolinar, Sam; Hamkins, Jon
2004-01-01
We present a scalable decoding architecture for a certain class of structured LDPC codes. The codes are designed using a small (n,r) protograph that is replicated Z times to produce a decoding graph for a (Z x n, Z x r) code. Using this architecture, we have implemented a decoder for a (4096,2048) LDPC code on a Xilinx Virtex-II 2000 FPGA, and achieved decoding speeds of 31 Mbps with 10 fixed iterations. The implemented message-passing algorithm uses an optimized 3-bit non-uniform quantizer that operates with 0.2dB implementation loss relative to a floating point decoder.
Decoding subjective mental states from fMRI activity patterns
International Nuclear Information System (INIS)
Tamaki, Masako; Kamitani, Yukiyasu
2011-01-01
In recent years, functional magnetic resonance imaging (fMRI) decoding has emerged as a powerful tool to read out detailed stimulus features from multi-voxel brain activity patterns. Moreover, the method has been extended to perform a primitive form of 'mind-reading,' by applying a decoder 'objectively' trained using stimulus features to more 'subjective' conditions. In this paper, we first introduce basic procedures for fMRI decoding based on machine learning techniques. Second, we discuss the source of information used for decoding, in particular, the possibility of extracting information from subvoxel neural structures. We next introduce two experimental designs for decoding subjective mental states: the 'objective-to-subjective design' and the 'subjective-to-subjective design.' Then, we illustrate recent studies on the decoding of a variety of mental states, such as, attention, awareness, decision making, memory, and mental imagery. Finally, we discuss the challenges and new directions of fMRI decoding. (author)
SYMBOL LEVEL DECODING FOR DUO-BINARY TURBO CODES
Directory of Open Access Journals (Sweden)
Yogesh Beeharry
2017-05-01
Full Text Available This paper investigates the performance of three different symbol level decoding algorithms for Duo-Binary Turbo codes. Explicit details of the computations involved in the three decoding techniques, and a computational complexity analysis are given. Simulation results with different couple lengths, code-rates, and QPSK modulation reveal that the symbol level decoding with bit-level information outperforms the symbol level decoding by 0.1 dB on average in the error floor region. Moreover, a complexity analysis reveals that symbol level decoding with bit-level information reduces the decoding complexity by 19.6 % in terms of the total number of computations required for each half-iteration as compared to symbol level decoding.
Belief propagation decoding of quantum channels by passing quantum messages
International Nuclear Information System (INIS)
Renes, Joseph M
2017-01-01
The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical–quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels. (fast track communication)
Belief propagation decoding of quantum channels by passing quantum messages
Renes, Joseph M.
2017-07-01
The belief propagation (BP) algorithm is a powerful tool in a wide range of disciplines from statistical physics to machine learning to computational biology, and is ubiquitous in decoding classical error-correcting codes. The algorithm works by passing messages between nodes of the factor graph associated with the code and enables efficient decoding of the channel, in some cases even up to the Shannon capacity. Here we construct the first BP algorithm which passes quantum messages on the factor graph and is capable of decoding the classical-quantum channel with pure state outputs. This gives explicit decoding circuits whose number of gates is quadratic in the code length. We also show that this decoder can be modified to work with polar codes for the pure state channel and as part of a decoder for transmitting quantum information over the amplitude damping channel. These represent the first explicit capacity-achieving decoders for non-Pauli channels.
Lin, Shu; Fossorier, Marc
1998-01-01
In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid
2013-04-04
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the \\\\textit{lattice decoder}. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid
2012-10-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
Video coding for decoding power-constrained embedded devices
Lu, Ligang; Sheinin, Vadim
2004-01-01
Low power dissipation and fast processing time are crucial requirements for embedded multimedia devices. This paper presents a technique in video coding to decrease the power consumption at a standard video decoder. Coupled with a small dedicated video internal memory cache on a decoder, the technique can substantially decrease the amount of data traffic to the external memory at the decoder. A decrease in data traffic to the external memory at decoder will result in multiple benefits: faster real-time processing and power savings. The encoder, given prior knowledge of the decoder"s dedicated video internal memory cache management scheme, regulates its choice of motion compensated predictors to reduce the decoder"s external memory accesses. This technique can be used in any standard or proprietary encoder scheme to generate a compliant output bit stream decodable by standard CPU-based and dedicated hardware-based decoders for power savings with the best quality-power cost trade off. Our simulation results show that with a relatively small amount of dedicated video internal memory cache, the technique may decrease the traffic between CPU and external memory over 50%.
On Lattice Sequential Decoding for The Unconstrained AWGN Channel
Abediseid, Walid; Alouini, Mohamed-Slim
2012-01-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter --- the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity.
Decoding spikes in a spiking neuronal network
Energy Technology Data Exchange (ETDEWEB)
Feng Jianfeng [Department of Informatics, University of Sussex, Brighton BN1 9QH (United Kingdom); Ding, Mingzhou [Department of Mathematics, Florida Atlantic University, Boca Raton, FL 33431 (United States)
2004-06-04
We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs.
Decoding spikes in a spiking neuronal network
International Nuclear Information System (INIS)
Feng Jianfeng; Ding, Mingzhou
2004-01-01
We investigate how to reliably decode the input information from the output of a spiking neuronal network. A maximum likelihood estimator of the input signal, together with its Fisher information, is rigorously calculated. The advantage of the maximum likelihood estimation over the 'brute-force rate coding' estimate is clearly demonstrated. It is pointed out that the ergodic assumption in neuroscience, i.e. a temporal average is equivalent to an ensemble average, is in general not true. Averaging over an ensemble of neurons usually gives a biased estimate of the input information. A method on how to compensate for the bias is proposed. Reconstruction of dynamical input signals with a group of spiking neurons is extensively studied and our results show that less than a spike is sufficient to accurately decode dynamical inputs
Neural decoding of visual imagery during sleep.
Horikawa, T; Tamaki, M; Miyawaki, Y; Kamitani, Y
2013-05-03
Visual imagery during sleep has long been a topic of persistent speculation, but its private nature has hampered objective analysis. Here we present a neural decoding approach in which machine-learning models predict the contents of visual imagery during the sleep-onset period, given measured brain activity, by discovering links between human functional magnetic resonance imaging patterns and verbal reports with the assistance of lexical and image databases. Decoding models trained on stimulus-induced brain activity in visual cortical areas showed accurate classification, detection, and identification of contents. Our findings demonstrate that specific visual experience during sleep is represented by brain activity patterns shared by stimulus perception, providing a means to uncover subjective contents of dreaming using objective neural measurement.
Power decoding Reed-Solomon codes up to the Johnson radius
DEFF Research Database (Denmark)
Rosenkilde, Johan Sebastian Heesemann
2018-01-01
Power decoding, or "decoding using virtual interleaving" is a technique for decoding Reed-Solomon codes up to the Sudan radius. Since the method's inception, it has been an open question if it is possible to use this approach to decode up to the Johnson radius - the decoding radius of the Guruswami...
Resource Efficient LDPC Decoders for Multimedia Communication
Chandrasetty, Vikram Arkalgud; Aziz, Syed Mahfuzul
2013-01-01
Achieving high image quality is an important aspect in an increasing number of wireless multimedia applications. These applications require resource efficient error correction hardware to detect and correct errors introduced by the communication channel. This paper presents an innovative flexible architecture for error correction using Low-Density Parity-Check (LDPC) codes. The proposed partially-parallel decoder architecture utilizes a novel code construction technique based on multi-level H...
Decoding divergent series in nonparaxial optics.
Borghi, Riccardo; Gori, Franco; Guattari, Giorgio; Santarsiero, Massimo
2011-03-15
A theoretical analysis aimed at investigating the divergent character of perturbative series involved in the study of free-space nonparaxial propagation of vectorial optical beams is proposed. Our analysis predicts a factorial divergence for such series and provides a theoretical framework within which the results of recently published numerical experiments concerning nonparaxial propagation of vectorial Gaussian beams find a meaningful interpretation in terms of the decoding operated on such series by the Weniger transformation.
Sequential decoders for large MIMO systems
Ali, Konpal S.
2014-05-01
Due to their ability to provide high data rates, multiple-input multiple-output (MIMO) systems have become increasingly popular. Decoding of these systems with acceptable error performance is computationally very demanding. In this paper, we employ the Sequential Decoder using the Fano Algorithm for large MIMO systems. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity and vice versa for higher bias values. Numerical results are done that show moderate bias values result in a decent performance-complexity trade-off. We also attempt to bound the error by bounding the bias, using the minimum distance of a lattice. The variations in complexity with SNR have an interesting trend that shows room for considerable improvement. Our work is compared against linear decoders (LDs) aided with Element-based Lattice Reduction (ELR) and Complex Lenstra-Lenstra-Lovasz (CLLL) reduction. © 2014 IFIP.
Markov source model for printed music decoding
Kopec, Gary E.; Chou, Philip A.; Maltz, David A.
1995-03-01
This paper describes a Markov source model for a simple subset of printed music notation. The model is based on the Adobe Sonata music symbol set and a message language of our own design. Chord imaging is the most complex part of the model. Much of the complexity follows from a rule of music typography that requires the noteheads for adjacent pitches to be placed on opposite sides of the chord stem. This rule leads to a proliferation of cases for other typographic details such as dot placement. We describe the language of message strings accepted by the model and discuss some of the imaging issues associated with various aspects of the message language. We also point out some aspects of music notation that appear problematic for a finite-state representation. Development of the model was greatly facilitated by the duality between image synthesis and image decoding. Although our ultimate objective was a music image model for use in decoding, most of the development proceeded by using the evolving model for image synthesis, since it is computationally far less costly to image a message than to decode an image.
Kernel Temporal Differences for Neural Decoding
Bae, Jihye; Sanchez Giraldo, Luis G.; Pohlmeyer, Eric A.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.
2015-01-01
We study the feasibility and capability of the kernel temporal difference (KTD)(λ) algorithm for neural decoding. KTD(λ) is an online, kernel-based learning algorithm, which has been introduced to estimate value functions in reinforcement learning. This algorithm combines kernel-based representations with the temporal difference approach to learning. One of our key observations is that by using strictly positive definite kernels, algorithm's convergence can be guaranteed for policy evaluation. The algorithm's nonlinear functional approximation capabilities are shown in both simulations of policy evaluation and neural decoding problems (policy improvement). KTD can handle high-dimensional neural states containing spatial-temporal information at a reasonable computational complexity allowing real-time applications. When the algorithm seeks a proper mapping between a monkey's neural states and desired positions of a computer cursor or a robot arm, in both open-loop and closed-loop experiments, it can effectively learn the neural state to action mapping. Finally, a visualization of the coadaptation process between the decoder and the subject shows the algorithm's capabilities in reinforcement learning brain machine interfaces. PMID:25866504
Deep Learning Methods for Improved Decoding of Linear Codes
Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair
2018-02-01
The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.
Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding
Douik, Ahmed
2016-06-27
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.
Decoding Delay Controlled Completion Time Reduction in Instantly Decodable Network Coding
Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
For several years, the completion time and the decoding delay problems in Instantly Decodable Network Coding (IDNC) were considered separately and were thought to act completely against each other. Recently, some works aimed to balance the effects of these two important IDNC metrics but none of them studied a further optimization of one by controlling the other. This paper investigates the effect of controlling the decoding delay to reduce the completion time below its currently best-known solution in both perfect and imperfect feedback with persistent erasure channels. To solve the problem, the decodingdelay- dependent expressions of the users’ and overall completion times are derived in the complete feedback scenario. Although using such expressions to find the optimal overall completion time is NP-hard, the paper proposes two novel heuristics that minimizes the probability of increasing the maximum of these decoding-delay-dependent completion time expressions after each transmission through a layered control of their decoding delays. Afterward, the paper extends the study to the imperfect feedback scenario in which uncertainties at the sender affects its ability to anticipate accurately the decoding delay increase at each user. The paper formulates the problem in such environment and derives the expression of the minimum increase in the completion time. Simulation results show the performance of the proposed solutions and suggest that both heuristics achieves a lower mean completion time as compared to the best-known heuristics for the completion time reduction in perfect and imperfect feedback. The gap in performance becomes more significant as the erasure of the channel increases.
Observations on Polar Coding with CRC-Aided List Decoding
2016-09-01
TECHNICAL REPORT 3041 September 2016 Observations on Polar Coding with CRC-Aided List Decoding David Wasserman Approved for public release. SSC...described in [2, 3]. In FY15 and FY16 we used cyclic redundancy check (CRC)-aided polar list decoding [4]. Section 2 describes the basics of polar coding ...and gives details of the encoders and decoders we used. In the course of our research, we performed simulations of polar codes in hundreds of cases
Polar Coding with CRC-Aided List Decoding
2015-08-01
TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536
A quantum algorithm for Viterbi decoding of classical convolutional codes
Grice, Jon R.; Meyer, David A.
2014-01-01
We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper the proposed algorithm is applied to decoding classical convolutional codes, for instance; large constraint length $Q$ and short decode frames $N$. Other applications of the classical Viterbi algorithm where $Q$ is large (e.g. speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butter...
Design of a VLSI Decoder for Partially Structured LDPC Codes
Directory of Open Access Journals (Sweden)
Fabrizio Vacca
2008-01-01
of their parity matrix can be partitioned into two disjoint sets, namely, the structured and the random ones. For the proposed class of codes a constructive design method is provided. To assess the value of this method the constructed codes performance are presented. From these results, a novel decoding method called split decoding is introduced. Finally, to prove the effectiveness of the proposed approach a whole VLSI decoder is designed and characterized.
Interpolation decoding method with variable parameters for fractal image compression
International Nuclear Information System (INIS)
He Chuanjiang; Li Gaoping; Shen Xiaona
2007-01-01
The interpolation fractal decoding method, which is introduced by [He C, Yang SX, Huang X. Progressive decoding method for fractal image compression. IEE Proc Vis Image Signal Process 2004;3:207-13], involves generating progressively the decoded image by means of an interpolation iterative procedure with a constant parameter. It is well-known that the majority of image details are added at the first steps of iterations in the conventional fractal decoding; hence the constant parameter for the interpolation decoding method must be set as a smaller value in order to achieve a better progressive decoding. However, it needs to take an extremely large number of iterations to converge. It is thus reasonable for some applications to slow down the iterative process at the first stages of decoding and then to accelerate it afterwards (e.g., at some iteration as we need). To achieve the goal, this paper proposed an interpolation decoding scheme with variable (iteration-dependent) parameters and proved the convergence of the decoding process mathematically. Experimental results demonstrate that the proposed scheme has really achieved the above-mentioned goal
Joint Decoding of Concatenated VLEC and STTC System
Directory of Open Access Journals (Sweden)
Chen Huijun
2008-01-01
Full Text Available Abstract We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.
Joint Decoding of Concatenated VLEC and STTC System
Directory of Open Access Journals (Sweden)
Huijun Chen
2008-07-01
Full Text Available We consider the decoding of wireless communication systems with both source coding in the application layer and channel coding in the physical layer for high-performance transmission over fading channels. Variable length error correcting codes (VLECs and space time trellis codes (STTCs are used to provide bandwidth efficient data compression as well as coding and diversity gains. At the receiver, an iterative joint source and space time decoding scheme are developed to utilize redundancy in both STTC and VLEC to improve overall decoding performance. Issues such as the inseparable systematic information in the symbol level, the asymmetric trellis structure of VLEC, and information exchange between bit and symbol domains have been considered in the maximum a posteriori probability (MAP decoding algorithm. Simulation results indicate that the developed joint decoding scheme achieves a significant decoding gain over the separate decoding in fading channels, whether or not the channel information is perfectly known at the receiver. Furthermore, how rate allocation between STTC and VLEC affects the performance of the joint source and space-time decoder is investigated. Different systems with a fixed overall information rate are studied. It is shown that for a system with more redundancy dedicated to the source code and a higher order modulation of STTC, the joint decoding yields better performance, though with increased complexity.
Grasp movement decoding from premotor and parietal cortex.
Townsend, Benjamin R; Subasi, Erk; Scherberger, Hansjörg
2011-10-05
Despite recent advances in harnessing cortical motor-related activity to control computer cursors and robotic devices, the ability to decode and execute different grasping patterns remains a major obstacle. Here we demonstrate a simple Bayesian decoder for real-time classification of grip type and wrist orientation in macaque monkeys that uses higher-order planning signals from anterior intraparietal cortex (AIP) and ventral premotor cortex (area F5). Real-time decoding was based on multiunit signals, which had similar tuning properties to cells in previous single-unit recording studies. Maximum decoding accuracy for two grasp types (power and precision grip) and five wrist orientations was 63% (chance level, 10%). Analysis of decoder performance showed that grip type decoding was highly accurate (90.6%), with most errors occurring during orientation classification. In a subsequent off-line analysis, we found small but significant performance improvements (mean, 6.25 percentage points) when using an optimized spike-sorting method (superparamagnetic clustering). Furthermore, we observed significant differences in the contributions of F5 and AIP for grasp decoding, with F5 being better suited for classification of the grip type and AIP contributing more toward decoding of object orientation. However, optimum decoding performance was maximal when using neural activity simultaneously from both areas. Overall, these results highlight quantitative differences in the functional representation of grasp movements in AIP and F5 and represent a first step toward using these signals for developing functional neural interfaces for hand grasping.
Sub-quadratic decoding of one-point hermitian codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde; Beelen, Peter
2015-01-01
We present the first two sub-quadratic complexity decoding algorithms for one-point Hermitian codes. The first is based on a fast realization of the Guruswami-Sudan algorithm using state-of-the-art algorithms from computer algebra for polynomial-ring matrix minimization. The second is a power...... decoding algorithm: an extension of classical key equation decoding which gives a probabilistic decoding algorithm up to the Sudan radius. We show how the resulting key equations can be solved by the matrix minimization algorithms from computer algebra, yielding similar asymptotic complexities....
Sudan-decoding generalized geometric Goppa codes
DEFF Research Database (Denmark)
Heydtmann, Agnes Eileen
2003-01-01
Generalized geometric Goppa codes are vector spaces of n-tuples with entries from different extension fields of a ground field. They are derived from evaluating functions similar to conventional geometric Goppa codes, but allowing evaluation in places of arbitrary degree. A decoding scheme...... for these codes based on Sudan's improved algorithm is presented and its error-correcting capacity is analyzed. For the implementation of the algorithm it is necessary that the so-called increasing zero bases of certain spaces of functions are available. A method to obtain such bases is developed....
Memory-efficient decoding of LDPC codes
Kwok-San Lee, Jason; Thorpe, Jeremy; Hawkins, Jon
2005-01-01
We present a low-complexity quantization scheme for the implementation of regular (3,6) LDPC codes. The quantization parameters are optimized to maximize the mutual information between the source and the quantized messages. Using this non-uniform quantized belief propagation algorithm, we have simulated that an optimized 3-bit quantizer operates with 0.2dB implementation loss relative to a floating point decoder, and an optimized 4-bit quantizer operates less than 0.1dB quantization loss.
[Modulation of Metacognition with Decoded Neurofeedback].
Koizumi, Ai; Cortese, Aurelio; Amano, Kaoru; Kawato, Mitsuo; Lau, Hakwan
2017-12-01
Humans often assess their confidence in their own perception, e.g., feeling "confident" or "certain" of having seen a friend, or feeling "uncertain" about whether the phone rang. The neural mechanism underlying the metacognitive function that reflects subjective perception still remains under debate. We have previously used decoded neurofeedback (DecNef) to demonstrate that manipulating the multivoxel activation patterns in the frontoparietal network modulates perceptual confidence without affecting perceptual performance. The results provided clear evidence for a dissociation between perceptual confidence and performance and suggested a distinct role of the frontoparietal network in metacognition.
Maximum a posteriori decoder for digital communications
Altes, Richard A. (Inventor)
1997-01-01
A system and method for decoding by identification of the most likely phase coded signal corresponding to received data. The present invention has particular application to communication with signals that experience spurious random phase perturbations. The generalized estimator-correlator uses a maximum a posteriori (MAP) estimator to generate phase estimates for correlation with incoming data samples and for correlation with mean phases indicative of unique hypothesized signals. The result is a MAP likelihood statistic for each hypothesized transmission, wherein the highest value statistic identifies the transmitted signal.
Vectorization of Reed Solomon decoding and mapping on the EVP
Kumar, A.; Berkel, van C.H.
2008-01-01
Reed Solomon (RS) codes are used in a variety of (wireless) communication systems. Although commonly implemented in dedicated hardware, this paper explores the mapping of high-throughput RS decoding on vector DSPs. The four modules of such a decoder, viz. Syndrome Computation, Key Equation Solver,
LDPC Codes--Structural Analysis and Decoding Techniques
Zhang, Xiaojie
2012-01-01
Low-density parity-check (LDPC) codes have been the focus of much research over the past decade thanks to their near Shannon limit performance and to their efficient message-passing (MP) decoding algorithms. However, the error floor phenomenon observed in MP decoding, which manifests itself as an abrupt change in the slope of the error-rate curve,…
IQ Predicts Word Decoding Skills in Populations with Intellectual Disabilities
Levy, Yonata
2011-01-01
This is a study of word decoding in adolescents with Down syndrome and in adolescents with Intellectual Deficits of unknown etiology. It was designed as a replication of studies of word decoding in English speaking and in Hebrew speaking adolescents with Williams syndrome ([0230] and [0235]). Participants' IQ was matched to IQ in the groups with…
Word Processing in Dyslexics: An Automatic Decoding Deficit?
Yap, Regina; Van Der Leu, Aryan
1993-01-01
Compares dyslexic children with normal readers on measures of phonological decoding and automatic word processing. Finds that dyslexics have a deficit in automatic phonological decoding skills. Discusses results within the framework of the phonological deficit and the automatization deficit hypotheses. (RS)
Role of Gender and Linguistic Diversity in Word Decoding Development
Verhoeven, Ludo; van Leeuwe, Jan
2011-01-01
The purpose of the present study was to investigate the role of gender and linguistic diversity in the growth of Dutch word decoding skills throughout elementary school for a representative sample of children living in the Netherlands. Following a longitudinal design, the children's decoding abilities for (1) regular CVC words, (2) complex…
Decoding bipedal locomotion from the rat sensorimotor cortex
Rigosa, J.; Panarese, A.; Dominici, N.; Friedli, L.; van den Brand, R.; Carpaneto, J.; DiGiovanna, J.; Courtine, G.; Micera, S.
2015-01-01
Objective. Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower
Multi-stage decoding of multi-level modulation codes
Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.
1991-01-01
Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).
Iterative List Decoding of Concatenated Source-Channel Codes
Directory of Open Access Journals (Sweden)
Hedayat Ahmadreza
2005-01-01
Full Text Available Whenever variable-length entropy codes are used in the presence of a noisy channel, any channel errors will propagate and cause significant harm. Despite using channel codes, some residual errors always remain, whose effect will get magnified by error propagation. Mitigating this undesirable effect is of great practical interest. One approach is to use the residual redundancy of variable length codes for joint source-channel decoding. In this paper, we improve the performance of residual redundancy source-channel decoding via an iterative list decoder made possible by a nonbinary outer CRC code. We show that the list decoding of VLC's is beneficial for entropy codes that contain redundancy. Such codes are used in state-of-the-art video coders, for example. The proposed list decoder improves the overall performance significantly in AWGN and fully interleaved Rayleigh fading channels.
Decoding magnetoencephalographic rhythmic activity using spectrospatial information.
Kauppi, Jukka-Pekka; Parkkonen, Lauri; Hari, Riitta; Hyvärinen, Aapo
2013-12-01
We propose a new data-driven decoding method called Spectral Linear Discriminant Analysis (Spectral LDA) for the analysis of magnetoencephalography (MEG). The method allows investigation of changes in rhythmic neural activity as a result of different stimuli and tasks. The introduced classification model only assumes that each "brain state" can be characterized as a combination of neural sources, each of which shows rhythmic activity at one or several frequency bands. Furthermore, the model allows the oscillation frequencies to be different for each such state. We present decoding results from 9 subjects in a four-category classification problem defined by an experiment involving randomly alternating epochs of auditory, visual and tactile stimuli interspersed with rest periods. The performance of Spectral LDA was very competitive compared with four alternative classifiers based on different assumptions concerning the organization of rhythmic brain activity. In addition, the spectral and spatial patterns extracted automatically on the basis of trained classifiers showed that Spectral LDA offers a novel and interesting way of analyzing spectrospatial oscillatory neural activity across the brain. All the presented classification methods and visualization tools are freely available as a Matlab toolbox. © 2013.
Unsupervised learning of facial emotion decoding skills
Directory of Open Access Journals (Sweden)
Jan Oliver Huelle
2014-02-01
Full Text Available Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practise without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear and sadness was shown in each clip. Although no external information about the correctness of the participant’s response or the sender’s true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practise effects often observed in cognitive tasks.
Unsupervised learning of facial emotion decoding skills.
Huelle, Jan O; Sack, Benjamin; Broer, Katja; Komlewa, Irina; Anders, Silke
2014-01-01
Research on the mechanisms underlying human facial emotion recognition has long focussed on genetically determined neural algorithms and often neglected the question of how these algorithms might be tuned by social learning. Here we show that facial emotion decoding skills can be significantly and sustainably improved by practice without an external teaching signal. Participants saw video clips of dynamic facial expressions of five different women and were asked to decide which of four possible emotions (anger, disgust, fear, and sadness) was shown in each clip. Although no external information about the correctness of the participant's response or the sender's true affective state was provided, participants showed a significant increase of facial emotion recognition accuracy both within and across two training sessions two days to several weeks apart. We discuss several similarities and differences between the unsupervised improvement of facial decoding skills observed in the current study, unsupervised perceptual learning of simple stimuli described in previous studies and practice effects often observed in cognitive tasks.
Decoding suprathreshold stochastic resonance with optimal weights
International Nuclear Information System (INIS)
Xu, Liyan; Vladusich, Tony; Duan, Fabing; Gunn, Lachlan J.; Abbott, Derek; McDonnell, Mark D.
2015-01-01
We investigate an array of stochastic quantizers for converting an analog input signal into a discrete output in the context of suprathreshold stochastic resonance. A new optimal weighted decoding is considered for different threshold level distributions. We show that for particular noise levels and choices of the threshold levels optimally weighting the quantizer responses provides a reduced mean square error in comparison with the original unweighted array. However, there are also many parameter regions where the original array provides near optimal performance, and when this occurs, it offers a much simpler approach than optimally weighting each quantizer's response. - Highlights: • A weighted summing array of independently noisy binary comparators is investigated. • We present an optimal linearly weighted decoding scheme for combining the comparator responses. • We solve for the optimal weights by applying least squares regression to simulated data. • We find that the MSE distortion of weighting before summation is superior to unweighted summation of comparator responses. • For some parameter regions, the decrease in MSE distortion due to weighting is negligible
Bayer image parallel decoding based on GPU
Hu, Rihui; Xu, Zhiyong; Wei, Yuxing; Sun, Shaohua
2012-11-01
In the photoelectrical tracking system, Bayer image is decompressed in traditional method, which is CPU-based. However, it is too slow when the images become large, for example, 2K×2K×16bit. In order to accelerate the Bayer image decoding, this paper introduces a parallel speedup method for NVIDA's Graphics Processor Unit (GPU) which supports CUDA architecture. The decoding procedure can be divided into three parts: the first is serial part, the second is task-parallelism part, and the last is data-parallelism part including inverse quantization, inverse discrete wavelet transform (IDWT) as well as image post-processing part. For reducing the execution time, the task-parallelism part is optimized by OpenMP techniques. The data-parallelism part could advance its efficiency through executing on the GPU as CUDA parallel program. The optimization techniques include instruction optimization, shared memory access optimization, the access memory coalesced optimization and texture memory optimization. In particular, it can significantly speed up the IDWT by rewriting the 2D (Tow-dimensional) serial IDWT into 1D parallel IDWT. Through experimenting with 1K×1K×16bit Bayer image, data-parallelism part is 10 more times faster than CPU-based implementation. Finally, a CPU+GPU heterogeneous decompression system was designed. The experimental result shows that it could achieve 3 to 5 times speed increase compared to the CPU serial method.
Squires, Katie Ellen
2013-01-01
This study investigated the differential contribution of auditory-verbal and visuospatial working memory (WM) on decoding skills in second- and fifth-grade children identified with poor decoding. Thirty-two second-grade students and 22 fifth-grade students completed measures that assessed simple and complex auditory-verbal and visuospatial memory,…
O2-GIDNC: Beyond instantly decodable network coding
Aboutorab, Neda
2013-06-01
In this paper, we are concerned with extending the graph representation of generalized instantly decodable network coding (GIDNC) to a more general opportunistic network coding (ONC) scenario, referred to as order-2 GIDNC (O2-GIDNC). In the O2-GIDNC scheme, receivers can store non-instantly decodable packets (NIDPs) comprising two of their missing packets, and use them in a systematic way for later decodings. Once this graph representation is found, it can be used to extend the GIDNC graph-based analyses to the proposed O2-GIDNC scheme with a limited increase in complexity. In the proposed O2-GIDNC scheme, the information of the stored NIDPs at the receivers and the decoding opportunities they create can be exploited to improve the broadcast completion time and decoding delay compared to traditional GIDNC scheme. The completion time and decoding delay minimizing algorithms that can operate on the new O2-GIDNC graph are further described. The simulation results show that our proposed O2-GIDNC improves the completion time and decoding delay performance of the traditional GIDNC. © 2013 IEEE.
On decoding of multi-level MPSK modulation codes
Lin, Shu; Gupta, Alok Kumar
1990-01-01
The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.
Encoder-decoder optimization for brain-computer interfaces.
Merel, Josh; Pianto, Donald M; Cunningham, John P; Paninski, Liam
2015-06-01
Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model") and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.
Encoder-decoder optimization for brain-computer interfaces.
Directory of Open Access Journals (Sweden)
Josh Merel
2015-06-01
Full Text Available Neuroprosthetic brain-computer interfaces are systems that decode neural activity into useful control signals for effectors, such as a cursor on a computer screen. It has long been recognized that both the user and decoding system can adapt to increase the accuracy of the end effector. Co-adaptation is the process whereby a user learns to control the system in conjunction with the decoder adapting to learn the user's neural patterns. We provide a mathematical framework for co-adaptation and relate co-adaptation to the joint optimization of the user's control scheme ("encoding model" and the decoding algorithm's parameters. When the assumptions of that framework are respected, co-adaptation cannot yield better performance than that obtainable by an optimal initial choice of fixed decoder, coupled with optimal user learning. For a specific case, we provide numerical methods to obtain such an optimized decoder. We demonstrate our approach in a model brain-computer interface system using an online prosthesis simulator, a simple human-in-the-loop pyschophysics setup which provides a non-invasive simulation of the BCI setting. These experiments support two claims: that users can learn encoders matched to fixed, optimal decoders and that, once learned, our approach yields expected performance advantages.
Hard decoding algorithm for optimizing thresholds under general Markovian noise
Chamberland, Christopher; Wallman, Joel; Beale, Stefanie; Laflamme, Raymond
2017-04-01
Quantum error correction is instrumental in protecting quantum systems from noise in quantum computing and communication settings. Pauli channels can be efficiently simulated and threshold values for Pauli error rates under a variety of error-correcting codes have been obtained. However, realistic quantum systems can undergo noise processes that differ significantly from Pauli noise. In this paper, we present an efficient hard decoding algorithm for optimizing thresholds and lowering failure rates of an error-correcting code under general completely positive and trace-preserving (i.e., Markovian) noise. We use our hard decoding algorithm to study the performance of several error-correcting codes under various non-Pauli noise models by computing threshold values and failure rates for these codes. We compare the performance of our hard decoding algorithm to decoders optimized for depolarizing noise and show improvements in thresholds and reductions in failure rates by several orders of magnitude. Our hard decoding algorithm can also be adapted to take advantage of a code's non-Pauli transversal gates to further suppress noise. For example, we show that using the transversal gates of the 5-qubit code allows arbitrary rotations around certain axes to be perfectly corrected. Furthermore, we show that Pauli twirling can increase or decrease the threshold depending upon the code properties. Lastly, we show that even if the physical noise model differs slightly from the hypothesized noise model used to determine an optimized decoder, failure rates can still be reduced by applying our hard decoding algorithm.
Decoding emotional valence from electroencephalographic rhythmic activity.
Celikkanat, Hande; Moriya, Hiroki; Ogawa, Takeshi; Kauppi, Jukka-Pekka; Kawanabe, Motoaki; Hyvarinen, Aapo
2017-07-01
We attempt to decode emotional valence from electroencephalographic rhythmic activity in a naturalistic setting. We employ a data-driven method developed in a previous study, Spectral Linear Discriminant Analysis, to discover the relationships between the classification task and independent neuronal sources, optimally utilizing multiple frequency bands. A detailed investigation of the classifier provides insight into the neuronal sources related with emotional valence, and the individual differences of the subjects in processing emotions. Our findings show: (1) sources whose locations are similar across subjects are consistently involved in emotional responses, with the involvement of parietal sources being especially significant, and (2) even though the locations of the involved neuronal sources are consistent, subjects can display highly varying degrees of valence-related EEG activity in the sources.
Decoding the mechanisms of Antikythera astronomical device
Lin, Jian-Liang
2016-01-01
This book presents a systematic design methodology for decoding the interior structure of the Antikythera mechanism, an astronomical device from ancient Greece. The historical background, surviving evidence and reconstructions of the mechanism are introduced, and the historical development of astronomical achievements and various astronomical instruments are investigated. Pursuing an approach based on the conceptual design of modern mechanisms and bearing in mind the standards of science and technology at the time, all feasible designs of the six lost/incomplete/unclear subsystems are synthesized as illustrated examples, and 48 feasible designs of the complete interior structure are presented. This approach provides not only a logical tool for applying modern mechanical engineering knowledge to the reconstruction of the Antikythera mechanism, but also an innovative research direction for identifying the original structures of the mechanism in the future. In short, the book offers valuable new insights for all...
Academic Training - Bioinformatics: Decoding the Genome
Chris Jones
2006-01-01
ACADEMIC TRAINING LECTURE SERIES 27, 28 February 1, 2, 3 March 2006 from 11:00 to 12:00 - Auditorium, bldg. 500 Decoding the Genome A special series of 5 lectures on: Recent extraordinary advances in the life sciences arising through new detection technologies and bioinformatics The past five years have seen an extraordinary change in the information and tools available in the life sciences. The sequencing of the human genome, the discovery that we possess far fewer genes than foreseen, the measurement of the tiny changes in the genomes that differentiate us, the sequencing of the genomes of many pathogens that lead to diseases such as malaria are all examples of completely new information that is now available in the quest for improved healthcare. New tools have allowed similar strides in the discovery of the associated protein structures, providing invaluable information for those searching for new drugs. New DNA microarray chips permit simultaneous measurement of the state of expression of tens...
Real-time minimal-bit-error probability decoding of convolutional codes
Lee, L.-N.
1974-01-01
A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.
Real-time minimal bit error probability decoding of convolutional codes
Lee, L. N.
1973-01-01
A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.
Multiple LDPC decoding for distributed source coding and video coding
DEFF Research Database (Denmark)
Forchhammer, Søren; Luong, Huynh Van; Huang, Xin
2011-01-01
Distributed source coding (DSC) is a coding paradigm for systems which fully or partly exploit the source statistics at the decoder to reduce the computational burden at the encoder. Distributed video coding (DVC) is one example. This paper considers the use of Low Density Parity Check Accumulate...... (LDPCA) codes in a DSC scheme with feed-back. To improve the LDPC coding performance in the context of DSC and DVC, while retaining short encoder blocks, this paper proposes multiple parallel LDPC decoding. The proposed scheme passes soft information between decoders to enhance performance. Experimental...
Locally decodable codes and private information retrieval schemes
Yekhanin, Sergey
2010-01-01
Locally decodable codes (LDCs) are codes that simultaneously provide efficient random access retrieval and high noise resilience by allowing reliable reconstruction of an arbitrary bit of a message by looking at only a small number of randomly chosen codeword bits. Local decodability comes with a certain loss in terms of efficiency - specifically, locally decodable codes require longer codeword lengths than their classical counterparts. Private information retrieval (PIR) schemes are cryptographic protocols designed to safeguard the privacy of database users. They allow clients to retrieve rec
Neural network decoder for quantum error correcting codes
Krastanov, Stefan; Jiang, Liang
Artificial neural networks form a family of extremely powerful - albeit still poorly understood - tools used in anything from image and sound recognition through text generation to, in our case, decoding. We present a straightforward Recurrent Neural Network architecture capable of deducing the correcting procedure for a quantum error-correcting code from a set of repeated stabilizer measurements. We discuss the fault-tolerance of our scheme and the cost of training the neural network for a system of a realistic size. Such decoders are especially interesting when applied to codes, like the quantum LDPC codes, that lack known efficient decoding schemes.
EXIT Chart Analysis of Binary Message-Passing Decoders
DEFF Research Database (Denmark)
Lechner, Gottfried; Pedersen, Troels; Kramer, Gerhard
2007-01-01
Binary message-passing decoders for LDPC codes are analyzed using EXIT charts. For the analysis, the variable node decoder performs all computations in the L-value domain. For the special case of a hard decision channel, this leads to the well know Gallager B algorithm, while the analysis can...... be extended to channels with larger output alphabets. By increasing the output alphabet from hard decisions to four symbols, a gain of more than 1.0 dB is achieved using optimized codes. For this code optimization, the mixing property of EXIT functions has to be modified to the case of binary message......-passing decoders....
Turbo decoder architecture for beyond-4G applications
Wong, Cheng-Chi
2013-01-01
This book describes the most recent techniques for turbo decoder implementation, especially for 4G and beyond 4G applications. The authors reveal techniques for the design of high-throughput decoders for future telecommunication systems, enabling designers to reduce hardware cost and shorten processing time. Coverage includes an explanation of VLSI implementation of the turbo decoder, from basic functional units to advanced parallel architecture. The authors discuss both hardware architecture techniques and experimental results, showing the variations in area/throughput/performance with respec
Encoding and Decoding Models in Cognitive Electrophysiology
Directory of Open Access Journals (Sweden)
Christopher R. Holdgraf
2017-09-01
Full Text Available Cognitive neuroscience has seen rapid growth in the size and complexity of data recorded from the human brain as well as in the computational tools available to analyze this data. This data explosion has resulted in an increased use of multivariate, model-based methods for asking neuroscience questions, allowing scientists to investigate multiple hypotheses with a single dataset, to use complex, time-varying stimuli, and to study the human brain under more naturalistic conditions. These tools come in the form of “Encoding” models, in which stimulus features are used to model brain activity, and “Decoding” models, in which neural features are used to generated a stimulus output. Here we review the current state of encoding and decoding models in cognitive electrophysiology and provide a practical guide toward conducting experiments and analyses in this emerging field. Our examples focus on using linear models in the study of human language and audition. We show how to calculate auditory receptive fields from natural sounds as well as how to decode neural recordings to predict speech. The paper aims to be a useful tutorial to these approaches, and a practical introduction to using machine learning and applied statistics to build models of neural activity. The data analytic approaches we discuss may also be applied to other sensory modalities, motor systems, and cognitive systems, and we cover some examples in these areas. In addition, a collection of Jupyter notebooks is publicly available as a complement to the material covered in this paper, providing code examples and tutorials for predictive modeling in python. The aim is to provide a practical understanding of predictive modeling of human brain data and to propose best-practices in conducting these analyses.
Study of bifurcation behavior of two-dimensional turbo product code decoders
International Nuclear Information System (INIS)
He Yejun; Lau, Francis C.M.; Tse, Chi K.
2008-01-01
Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values
Study of bifurcation behavior of two-dimensional turbo product code decoders
Energy Technology Data Exchange (ETDEWEB)
He Yejun [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China); Lau, Francis C.M. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)], E-mail: encmlau@polyu.edu.hk; Tse, Chi K. [Department of Electronic and Information Engineering, Hong Kong Polytechnic University, Hunghom, Hong Kong (China)
2008-04-15
Turbo codes, low-density parity-check (LDPC) codes and turbo product codes (TPCs) are high performance error-correction codes which employ iterative algorithms for decoding. Under different conditions, the behaviors of the decoders are different. While the nonlinear dynamical behaviors of turbo code decoders and LDPC decoders have been reported in the literature, the dynamical behavior of TPC decoders is relatively unexplored. In this paper, we investigate the behavior of the iterative algorithm of a two-dimensional TPC decoder when the input signal-to-noise ratio (SNR) varies. The quantity to be measured is the mean square value of the posterior probabilities of the information bits. Unlike turbo decoders or LDPC decoders, TPC decoders do not produce a clear 'waterfall region'. This is mainly because the TPC decoding algorithm does not converge to 'indecisive' fixed points even at very low SNR values.
Architecture for time or transform domain decoding of reed-solomon codes
Shao, Howard M. (Inventor); Truong, Trieu-Kie (Inventor); Hsu, In-Shek (Inventor); Deutsch, Leslie J. (Inventor)
1989-01-01
Two pipeline (255,233) RS decoders, one a time domain decoder and the other a transform domain decoder, use the same first part to develop an errata locator polynomial .tau.(x), and an errata evaluator polynominal A(x). Both the time domain decoder and transform domain decoder have a modified GCD that uses an input multiplexer and an output demultiplexer to reduce the number of GCD cells required. The time domain decoder uses a Chien search and polynomial evaluator on the GCD outputs .tau.(x) and A(x), for the final decoding steps, while the transform domain decoder uses a transform error pattern algorithm operating on .tau.(x) and the initial syndrome computation S(x), followed by an inverse transform algorithm in sequence for the final decoding steps prior to adding the received RS coded message to produce a decoded output message.
Construction and decoding of a class of algebraic geometry codes
DEFF Research Database (Denmark)
Justesen, Jørn; Larsen, Knud J.; Jensen, Helge Elbrønd
1989-01-01
A class of codes derived from algebraic plane curves is constructed. The concepts and results from algebraic geometry that were used are explained in detail; no further knowledge of algebraic geometry is needed. Parameters, generator and parity-check matrices are given. The main result is a decod...... is a decoding algorithm which turns out to be a generalization of the Peterson algorithm for decoding BCH decoder codes......A class of codes derived from algebraic plane curves is constructed. The concepts and results from algebraic geometry that were used are explained in detail; no further knowledge of algebraic geometry is needed. Parameters, generator and parity-check matrices are given. The main result...
Toward a universal decoder of linguistic meaning from brain activation.
Pereira, Francisco; Lou, Bin; Pritchett, Brianna; Ritter, Samuel; Gershman, Samuel J; Kanwisher, Nancy; Botvinick, Matthew; Fedorenko, Evelina
2018-03-06
Prior work decoding linguistic meaning from imaging data has been largely limited to concrete nouns, using similar stimuli for training and testing, from a relatively small number of semantic categories. Here we present a new approach for building a brain decoding system in which words and sentences are represented as vectors in a semantic space constructed from massive text corpora. By efficiently sampling this space to select training stimuli shown to subjects, we maximize the ability to generalize to new meanings from limited imaging data. To validate this approach, we train the system on imaging data of individual concepts, and show it can decode semantic vector representations from imaging data of sentences about a wide variety of both concrete and abstract topics from two separate datasets. These decoded representations are sufficiently detailed to distinguish even semantically similar sentences, and to capture the similarity structure of meaning relationships between sentences.
Illustrative examples in a bilingual decoding dictionary: An (un ...
African Journals Online (AJOL)
Keywords: Illustrative Examples, Bilingual Decoding Dictionary, Semantic Differences Between Source Language (Sl) And Target Language (Tl), Grammatical Differences Between Sl And Tl, Translation Of Examples, Transposition, Context-Dependent Translation, One-Word Equivalent, Zero Equivalent, Idiomatic ...
Decoding Reed-Solomon Codes beyond half the minimum distance
DEFF Research Database (Denmark)
Høholdt, Tom; Nielsen, Rasmus Refslund
1999-01-01
We describe an efficient implementation of M.Sudan"s algorithm for decoding Reed-Solomon codes beyond half the minimum distance. Furthermore we calculate an upper bound of the probabilty of getting more than one codeword as output...
An overview of turbo decoding on fading channels
ATILGAN, Doğan
2009-01-01
A review of turbo coding and decoding has been presented in the literature [1]. In that paper, turbo coding and decoding on AWGN (Additive White Gaussian Noise) channels has been elaborated. In wireless communications, a phenomennon called multipath fading is frequently encountered. Therefore, investigation of efficient techniques to tackle with the destructive effects of fading is essential. Turbo coding has been proven as an efficient channel coding technique for AWGN channels. Some of the ...
Performance Analysis of a Decoding Algorithm for Algebraic Geometry Codes
DEFF Research Database (Denmark)
Jensen, Helge Elbrønd; Nielsen, Rasmus Refslund; Høholdt, Tom
1998-01-01
We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is greater than or equal to [(dFR-1)/2]+1, where dFR is the Feng-Rao distance......We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is greater than or equal to [(dFR-1)/2]+1, where dFR is the Feng-Rao distance...
Recent results in the decoding of Algebraic geometry codes
DEFF Research Database (Denmark)
Høholdt, Tom; Jensen, Helge Elbrønd; Nielsen, Rasmus Refslund
1998-01-01
We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is [(dFR-1)/2]+1, where dFR is the Feng-Rao distance......We analyse the known decoding algorithms for algebraic geometry codes in the case where the number of errors is [(dFR-1)/2]+1, where dFR is the Feng-Rao distance...
Effect of video decoder errors on video interpretability
Young, Darrell L.
2014-06-01
The advancement in video compression technology can result in more sensitivity to bit errors. Bit errors can propagate causing sustained loss of interpretability. In the worst case, the decoder "freezes" until it can re-synchronize with the stream. Detection of artifacts enables downstream processes to avoid corrupted frames. A simple template approach to detect block stripes and a more advanced cascade approach to detect compression artifacts was shown to correlate to the presence of artifacts and decoder messages.
Electrophysiological difference between mental state decoding and mental state reasoning.
Cao, Bihua; Li, Yiyuan; Li, Fuhong; Li, Hong
2012-06-29
Previous studies have explored the neural mechanism of Theory of Mind (ToM), but the neural correlates of its two components, mental state decoding and mental state reasoning, remain unclear. In the present study, participants were presented with various photographs, showing an actor looking at 1 of 2 objects, either with a happy or an unhappy expression. They were asked to either decode the emotion of the actor (mental state decoding task), predict which object would be chosen by the actor (mental state reasoning task), or judge at which object the actor was gazing (physical task), while scalp potentials were recorded. Results showed that (1) the reasoning task elicited an earlier N2 peak than the decoding task did over the prefrontal scalp sites; and (2) during the late positive component (240-440 ms), the reasoning task elicited a more positive deflection than the other two tasks did at the prefrontal scalp sites. In addition, neither the decoding task nor the reasoning task has no left/right hemisphere difference. These findings imply that mental state reasoning differs from mental state decoding early (210 ms) after stimulus onset, and that the prefrontal lobe is the neural basis of mental state reasoning. Copyright © 2012 Elsevier B.V. All rights reserved.
Evaluation framework for K-best sphere decoders
Shen, Chungan
2010-08-01
While Maximum-Likelihood (ML) is the optimum decoding scheme for most communication scenarios, practical implementation difficulties limit its use, especially for Multiple Input Multiple Output (MIMO) systems with a large number of transmit or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature with widely varying performance to area and power metrics. In this semi-tutorial paper we present a holistic view of different Sphere decoding techniques and K-best decoding techniques, identifying the key algorithmic and implementation trade-offs. We establish a consistent benchmark framework to investigate and compare the delay cost, power cost, and power-delay-product cost incurred by each method. Finally, using the framework, we propose and analyze a novel architecture and compare that to other published approaches. Our goal is to explicitly elucidate the overall advantages and disadvantages of each proposed algorithms in one coherent framework. © 2010 World Scientific Publishing Company.
Partially blind instantly decodable network codes for lossy feedback environment
Sorour, Sameh
2014-09-01
In this paper, we study the multicast completion and decoding delay minimization problems for instantly decodable network coding (IDNC) in the case of lossy feedback. When feedback loss events occur, the sender falls into uncertainties about packet reception at the different receivers, which forces it to perform partially blind selections of packet combinations in subsequent transmissions. To determine efficient selection policies that reduce the completion and decoding delays of IDNC in such an environment, we first extend the perfect feedback formulation in our previous works to the lossy feedback environment, by incorporating the uncertainties resulting from unheard feedback events in these formulations. For the completion delay problem, we use this formulation to identify the maximum likelihood state of the network in events of unheard feedback and employ it to design a partially blind graph update extension to the multicast IDNC algorithm in our earlier work. For the decoding delay problem, we derive an expression for the expected decoding delay increment for any arbitrary transmission. This expression is then used to find the optimal policy that reduces the decoding delay in such lossy feedback environment. Results show that our proposed solutions both outperform previously proposed approaches and achieve tolerable degradation even at relatively high feedback loss rates.
Lei, Ted Chih-Wei; Tseng, Fan-Shuo
2017-07-01
This paper addresses the problem of high-computational complexity decoding in traditional Wyner-Ziv video coding (WZVC). The key focus is the migration of two traditionally high-computationally complex encoder algorithms, namely motion estimation and mode decision. In order to reduce the computational burden in this process, the proposed architecture adopts the partial boundary matching algorithm and four flexible types of block mode decision at the decoder. This approach does away with the need for motion estimation and mode decision at the encoder. The experimental results show that the proposed padding block-based WZVC not only decreases decoder complexity to approximately one hundredth that of the state-of-the-art DISCOVER decoding but also outperforms DISCOVER codec by up to 3 to 4 dB.
Singer product apertures—A coded aperture system with a fast decoding algorithm
International Nuclear Information System (INIS)
Byard, Kevin; Shutler, Paul M.E.
2017-01-01
A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.
An FPGA Implementation of (3,6-Regular Low-Density Parity-Check Code Decoder
Directory of Open Access Journals (Sweden)
Tong Zhang
2003-05-01
Full Text Available Because of their excellent error-correcting performance, low-density parity-check (LDPC codes have recently attracted a lot of attention. In this paper, we are interested in the practical LDPC code decoder hardware implementations. The direct fully parallel decoder implementation usually incurs too high hardware complexity for many real applications, thus partly parallel decoder design approaches that can achieve appropriate trade-offs between hardware complexity and decoding throughput are highly desirable. Applying a joint code and decoder design methodology, we develop a high-speed (3,k-regular LDPC code partly parallel decoder architecture based on which we implement a 9216-bit, rate-1/2(3,6-regular LDPC code decoder on Xilinx FPGA device. This partly parallel decoder supports a maximum symbol throughput of 54 Mbps and achieves BER 10Ã¢ÂˆÂ’6 at 2 dB over AWGN channel while performing maximum 18 decoding iterations.
Singer product apertures—A coded aperture system with a fast decoding algorithm
Energy Technology Data Exchange (ETDEWEB)
Byard, Kevin, E-mail: kevin.byard@aut.ac.nz [School of Economics, Faculty of Business, Economics and Law, Auckland University of Technology, Auckland 1142 (New Zealand); Shutler, Paul M.E. [National Institute of Education, Nanyang Technological University, 1 Nanyang Walk, Singapore 637616 (Singapore)
2017-06-01
A new type of coded aperture configuration that enables fast decoding of the coded aperture shadowgram data is presented. Based on the products of incidence vectors generated from the Singer difference sets, we call these Singer product apertures. For a range of aperture dimensions, we compare experimentally the performance of three decoding methods: standard decoding, induction decoding and direct vector decoding. In all cases the induction and direct vector methods are several orders of magnitude faster than the standard method, with direct vector decoding being significantly faster than induction decoding. For apertures of the same dimensions the increase in speed offered by direct vector decoding over induction decoding is better for lower throughput apertures.
Decoding reality the universe as quantum information
Vedral, Vlatko
2010-01-01
In Decoding Reality, Vlatko Vedral offers a mind-stretching look at the deepest questions about the universe--where everything comes from, why things are as they are, what everything is. The most fundamental definition of reality is not matter or energy, he writes, but information--and it is the processing of information that lies at the root of all physical, biological, economic, and social phenomena. This view allows Vedral to address a host of seemingly unrelated questions: Why does DNA bind like it does? What is the ideal diet for longevity? How do you make your first million dollars? We can unify all through the understanding that everything consists of bits of information, he writes, though that raises the question of where these bits come from. To find the answer, he takes us on a guided tour through the bizarre realm of quantum physics. At this sub-sub-subatomic level, we find such things as the interaction of separated quantum particles--what Einstein called "spooky action at a distance." In fact, V...
Statistical coding and decoding of heartbeat intervals.
Lucena, Fausto; Barros, Allan Kardec; Príncipe, José C; Ohnishi, Noboru
2011-01-01
The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.
Rate Aware Instantly Decodable Network Codes
Douik, Ahmed
2016-02-26
This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.
Encoding and decoding messages with chaotic lasers
International Nuclear Information System (INIS)
Alsing, P.M.; Gavrielides, A.; Kovanis, V.; Roy, R.; Thornburg, K.S. Jr.
1997-01-01
We investigate the structure of the strange attractor of a chaotic loss-modulated solid-state laser utilizing return maps based on a combination of intensity maxima and interspike intervals, as opposed to those utilizing Poincare sections defined by the intensity maxima of the laser (I=0,Ie<0) alone. We find both experimentally and numerically that a simple, intrinsic relationship exists between an intensity maximum and the pair of preceding and succeeding interspike intervals. In addition, we numerically investigate encoding messages on the output of a chaotic transmitter laser and its subsequent decoding by a similar receiver laser. By exploiting the relationship between the intensity maxima and the interspike intervals, we demonstrate that the method utilized to encode the message is vital to the system close-quote s ability to hide the signal from unwanted deciphering. In this work alternative methods are studied in order to encode messages by modulating the magnitude of pumping of the transmitter laser and also by driving its loss modulation with more than one frequency. copyright 1997 The American Physical Society
Fast mental states decoding in mixed reality.
Directory of Open Access Journals (Sweden)
Daniele eDe Massari
2014-11-01
Full Text Available The combination of Brain-Computer Interface technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. In this context, assessing to what extent brain states can be discriminated during mixed reality experience is critical for adapting specific data features to contingent brain activity. In this study we recorded EEG data while participants experienced a mixed reality scenario implemented through the eXperience Induction Machine (XIM. The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in mixed reality, using LDA and SVM classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled mixed reality scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in mixed reality.
Decoding P4-ATPase substrate interactions.
Roland, Bartholomew P; Graham, Todd R
Cellular membranes display a diversity of functions that are conferred by the unique composition and organization of their proteins and lipids. One important aspect of lipid organization is the asymmetric distribution of phospholipids (PLs) across the plasma membrane. The unequal distribution of key PLs between the cytofacial and exofacial leaflets of the bilayer creates physical surface tension that can be used to bend the membrane; and like Ca 2+ , a chemical gradient that can be used to transduce biochemical signals. PL flippases in the type IV P-type ATPase (P4-ATPase) family are the principle transporters used to set and repair this PL gradient and the asymmetric organization of these membranes are encoded by the substrate specificity of these enzymes. Thus, understanding the mechanisms of P4-ATPase substrate specificity will help reveal their role in membrane organization and cell biology. Further, decoding the structural determinants of substrate specificity provides investigators the opportunity to mutationally tune this specificity to explore the role of particular PL substrates in P4-ATPase cellular functions. This work reviews the role of P4-ATPases in membrane biology, presents our current understanding of P4-ATPase substrate specificity, and discusses how these fundamental aspects of P4-ATPase enzymology may be used to enhance our knowledge of cellular membrane biology.
Fast mental states decoding in mixed reality.
De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F M J; Birbaumer, Niels; Caria, Andrea
2014-01-01
The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR.
Observing human movements helps decoding environmental forces.
Zago, Myrka; La Scaleia, Barbara; Miller, William L; Lacquaniti, Francesco
2011-11-01
Vision of human actions can affect several features of visual motion processing, as well as the motor responses of the observer. Here, we tested the hypothesis that action observation helps decoding environmental forces during the interception of a decelerating target within a brief time window, a task intrinsically very difficult. We employed a factorial design to evaluate the effects of scene orientation (normal or inverted) and target gravity (normal or inverted). Button-press triggered the motion of a bullet, a piston, or a human arm. We found that the timing errors were smaller for upright scenes irrespective of gravity direction in the Bullet group, while the errors were smaller for the standard condition of normal scene and gravity in the Piston group. In the Arm group, instead, performance was better when the directions of scene and target gravity were concordant, irrespective of whether both were upright or inverted. These results suggest that the default viewer-centered reference frame is used with inanimate scenes, such as those of the Bullet and Piston protocols. Instead, the presence of biological movements in animate scenes (as in the Arm protocol) may help processing target kinematics under the ecological conditions of coherence between scene and target gravity directions.
Rate Aware Instantly Decodable Network Codes
Douik, Ahmed; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
This paper addresses the problem of reducing the delivery time of data messages to cellular users using instantly decodable network coding (IDNC) with physical-layer rate awareness. While most of the existing literature on IDNC does not consider any physical layer complications, this paper proposes a cross-layer scheme that incorporates the different channel rates of the various users in the decision process of both the transmitted message combinations and the rates with which they are transmitted. The completion time minimization problem in such scenario is first shown to be intractable. The problem is, thus, approximated by reducing, at each transmission, the increase of an anticipated version of the completion time. The paper solves the problem by formulating it as a maximum weight clique problem over a newly designed rate aware IDNC (RA-IDNC) graph. Further, the paper provides a multi-layer solution to improve the completion time approximation. Simulation results suggest that the cross-layer design largely outperforms the uncoded transmissions strategies and the classical IDNC scheme. © 2015 IEEE.
Statistical coding and decoding of heartbeat intervals.
Directory of Open Access Journals (Sweden)
Fausto Lucena
Full Text Available The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.
Efficient universal computing architectures for decoding neural activity.
Directory of Open Access Journals (Sweden)
Benjamin I Rapoport
Full Text Available The ability to decode neural activity into meaningful control signals for prosthetic devices is critical to the development of clinically useful brain- machine interfaces (BMIs. Such systems require input from tens to hundreds of brain-implanted recording electrodes in order to deliver robust and accurate performance; in serving that primary function they should also minimize power dissipation in order to avoid damaging neural tissue; and they should transmit data wirelessly in order to minimize the risk of infection associated with chronic, transcutaneous implants. Electronic architectures for brain- machine interfaces must therefore minimize size and power consumption, while maximizing the ability to compress data to be transmitted over limited-bandwidth wireless channels. Here we present a system of extremely low computational complexity, designed for real-time decoding of neural signals, and suited for highly scalable implantable systems. Our programmable architecture is an explicit implementation of a universal computing machine emulating the dynamics of a network of integrate-and-fire neurons; it requires no arithmetic operations except for counting, and decodes neural signals using only computationally inexpensive logic operations. The simplicity of this architecture does not compromise its ability to compress raw neural data by factors greater than [Formula: see text]. We describe a set of decoding algorithms based on this computational architecture, one designed to operate within an implanted system, minimizing its power consumption and data transmission bandwidth; and a complementary set of algorithms for learning, programming the decoder, and postprocessing the decoded output, designed to operate in an external, nonimplanted unit. The implementation of the implantable portion is estimated to require fewer than 5000 operations per second. A proof-of-concept, 32-channel field-programmable gate array (FPGA implementation of this portion
A real-time MPEG software decoder using a portable message-passing library
Energy Technology Data Exchange (ETDEWEB)
Kwong, Man Kam; Tang, P.T. Peter; Lin, Biquan
1995-12-31
We present a real-time MPEG software decoder that uses message-passing libraries such as MPL, p4 and MPI. The parallel MPEG decoder currently runs on the IBM SP system but can be easil ported to other parallel machines. This paper discusses our parallel MPEG decoding algorithm as well as the parallel programming environment under which it uses. Several technical issues are discussed, including balancing of decoding speed, memory limitation, 1/0 capacities, and optimization of MPEG decoding components. This project shows that a real-time portable software MPEG decoder is feasible in a general-purpose parallel machine.
Mapping visual stimuli to perceptual decisions via sparse decoding of mesoscopic neural activity.
Sajda, Paul
2010-01-01
In this talk I will describe our work investigating sparse decoding of neural activity, given a realistic mapping of the visual scene to neuronal spike trains generated by a model of primary visual cortex (V1). We use a linear decoder which imposes sparsity via an L1 norm. The decoder can be viewed as a decoding neuron (linear summation followed by a sigmoidal nonlinearity) in which there are relatively few non-zero synaptic weights. We find: (1) the best decoding performance is for a representation that is sparse in both space and time, (2) decoding of a temporal code results in better performance than a rate code and is also a better fit to the psychophysical data, (3) the number of neurons required for decoding increases monotonically as signal-to-noise in the stimulus decreases, with as little as 1% of the neurons required for decoding at the highest signal-to-noise levels, and (4) sparse decoding results in a more accurate decoding of the stimulus and is a better fit to psychophysical performance than a distributed decoding, for example one imposed by an L2 norm. We conclude that sparse coding is well-justified from a decoding perspective in that it results in a minimum number of neurons and maximum accuracy when sparse representations can be decoded from the neural dynamics.
Robust pattern decoding in shape-coded structured light
Tang, Suming; Zhang, Xu; Song, Zhan; Song, Lifang; Zeng, Hai
2017-09-01
Decoding is a challenging and complex problem in a coded structured light system. In this paper, a robust pattern decoding method is proposed for the shape-coded structured light in which the pattern is designed as grid shape with embedded geometrical shapes. In our decoding method, advancements are made at three steps. First, a multi-template feature detection algorithm is introduced to detect the feature point which is the intersection of each two orthogonal grid-lines. Second, pattern element identification is modelled as a supervised classification problem and the deep neural network technique is applied for the accurate classification of pattern elements. Before that, a training dataset is established, which contains a mass of pattern elements with various blurring and distortions. Third, an error correction mechanism based on epipolar constraint, coplanarity constraint and topological constraint is presented to reduce the false matches. In the experiments, several complex objects including human hand are chosen to test the accuracy and robustness of the proposed method. The experimental results show that our decoding method not only has high decoding accuracy, but also owns strong robustness to surface color and complex textures.
Optimal and efficient decoding of concatenated quantum block codes
International Nuclear Information System (INIS)
Poulin, David
2006-01-01
We consider the problem of optimally decoding a quantum error correction code--that is, to find the optimal recovery procedure given the outcomes of partial ''check'' measurements on the system. In general, this problem is NP hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message-passing algorithm. We compare the performance of the message-passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the five-qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message-passing algorithms in two respects: (i) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel; and (ii) for noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead
Distributed coding/decoding complexity in video sensor networks.
Cordeiro, Paulo J; Assunção, Pedro
2012-01-01
Video Sensor Networks (VSNs) are recent communication infrastructures used to capture and transmit dense visual information from an application context. In such large scale environments which include video coding, transmission and display/storage, there are several open problems to overcome in practical implementations. This paper addresses the most relevant challenges posed by VSNs, namely stringent bandwidth usage and processing time/power constraints. In particular, the paper proposes a novel VSN architecture where large sets of visual sensors with embedded processors are used for compression and transmission of coded streams to gateways, which in turn transrate the incoming streams and adapt them to the variable complexity requirements of both the sensor encoders and end-user decoder terminals. Such gateways provide real-time transcoding functionalities for bandwidth adaptation and coding/decoding complexity distribution by transferring the most complex video encoding/decoding tasks to the transcoding gateway at the expense of a limited increase in bit rate. Then, a method to reduce the decoding complexity, suitable for system-on-chip implementation, is proposed to operate at the transcoding gateway whenever decoders with constrained resources are targeted. The results show that the proposed method achieves good performance and its inclusion into the VSN infrastructure provides an additional level of complexity control functionality.
Lexical decoder for continuous speech recognition: sequential neural network approach
International Nuclear Information System (INIS)
Iooss, Christine
1991-01-01
The work presented in this dissertation concerns the study of a connectionist architecture to treat sequential inputs. In this context, the model proposed by J.L. Elman, a recurrent multilayers network, is used. Its abilities and its limits are evaluated. Modifications are done in order to treat erroneous or noisy sequential inputs and to classify patterns. The application context of this study concerns the realisation of a lexical decoder for analytical multi-speakers continuous speech recognition. Lexical decoding is completed from lattices of phonemes which are obtained after an acoustic-phonetic decoding stage relying on a K Nearest Neighbors search technique. Test are done on sentences formed from a lexicon of 20 words. The results are obtained show the ability of the proposed connectionist model to take into account the sequentiality at the input level, to memorize the context and to treat noisy or erroneous inputs. (author) [fr
Systolic array processing of the sequential decoding algorithm
Chang, C. Y.; Yao, K.
1989-01-01
A systolic array processing technique is applied to implementing the stack algorithm form of the sequential decoding algorithm. It is shown that sorting, a key function in the stack algorithm, can be efficiently realized by a special type of systolic arrays known as systolic priority queues. Compared to the stack-bucket algorithm, this approach is shown to have the advantages that the decoding always moves along the optimal path, that it has a fast and constant decoding speed and that its simple and regular hardware architecture is suitable for VLSI implementation. Three types of systolic priority queues are discussed: random access scheme, shift register scheme and ripple register scheme. The property of the entries stored in the systolic priority queue is also investigated. The results are applicable to many other basic sorting type problems.
Analysis of Minimal LDPC Decoder System on a Chip Implementation
Directory of Open Access Journals (Sweden)
T. Palenik
2015-09-01
Full Text Available This paper presents a practical method of potential replacement of several different Quasi-Cyclic Low-Density Parity-Check (QC-LDPC codes with one, with the intention of saving as much memory as required to implement the LDPC encoder and decoder in a memory-constrained System on a Chip (SoC. The presented method requires only a very small modification of the existing encoder and decoder, making it suitable for utilization in a Software Defined Radio (SDR platform. Besides the analysis of the effects of necessary variable-node value fixation during the Belief Propagation (BP decoding algorithm, practical standard-defined code parameters are scrutinized in order to evaluate the feasibility of the proposed LDPC setup simplification. Finally, the error performance of the modified system structure is evaluated and compared with the original system structure by means of simulation.
Analysis and Design of Binary Message-Passing Decoders
DEFF Research Database (Denmark)
Lechner, Gottfried; Pedersen, Troels; Kramer, Gerhard
2012-01-01
Binary message-passing decoders for low-density parity-check (LDPC) codes are studied by using extrinsic information transfer (EXIT) charts. The channel delivers hard or soft decisions and the variable node decoder performs all computations in the L-value domain. A hard decision channel results...... message-passing decoders. Finally, it is shown that errors on cycles consisting only of degree two and three variable nodes cannot be corrected and a necessary and sufficient condition for the existence of a cycle-free subgraph is derived....... in the well-know Gallager B algorithm, and increasing the output alphabet from hard decisions to two bits yields a gain of more than 1.0 dB in the required signal to noise ratio when using optimized codes. The code optimization requires adapting the mixing property of EXIT functions to the case of binary...
Error-correction coding and decoding bounds, codes, decoders, analysis and applications
Tomlinson, Martin; Ambroze, Marcel A; Ahmed, Mohammed; Jibril, Mubarak
2017-01-01
This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style, the book presents the authors’ twenty-five years of research organized into five parts: Part I is concerned with the theoretical performance attainable by using error correcting codes to achieve communications efficiency in digital communications systems. Part II explores the construction of error-correcting codes and explains the different families of codes and how they are designed. Techniques are described for producing the very best codes. Part III addresses the analysis of low-density parity-check (LDPC) codes, primarily to calculate their stopping sets and low-weight codeword spectrum which determines the performance of these codes. Part IV deals with decoders desi...
The fast decoding of Reed-Solomon codes using Fermat theoretic transforms and continued fractions
Reed, I. S.; Scholtz, R. A.; Welch, L. R.; Truong, T. K.
1978-01-01
It is shown that Reed-Solomon (RS) codes can be decoded by using a fast Fourier transform (FFT) algorithm over finite fields GF(F sub n), where F sub n is a Fermat prime, and continued fractions. This new transform decoding method is simpler than the standard method for RS codes. The computing time of this new decoding algorithm in software can be faster than the standard decoding method for RS codes.
Joint Estimation and Decoding of Space-Time Trellis Codes
Directory of Open Access Journals (Sweden)
Zhang Jianqiu
2002-01-01
Full Text Available We explore the possibility of using an emerging tool in statistical signal processing, sequential importance sampling (SIS, for joint estimation and decoding of space-time trellis codes (STTC. First, we provide background on SIS, and then we discuss its application to space-time trellis code (STTC systems. It is shown through simulations that SIS is suitable for joint estimation and decoding of STTC with time-varying flat-fading channels when phase ambiguity is avoided. We used a design criterion for STTCs and temporally correlated channels that combats phase ambiguity without pilot signaling. We have shown by simulations that the design is valid.
Efficient decoding of random errors for quantum expander codes
Fawzi , Omar; Grospellier , Antoine; Leverrier , Anthony
2017-01-01
We show that quantum expander codes, a constant-rate family of quantum LDPC codes, with the quasi-linear time decoding algorithm of Leverrier, Tillich and Z\\'emor can correct a constant fraction of random errors with very high probability. This is the first construction of a constant-rate quantum LDPC code with an efficient decoding algorithm that can correct a linear number of random errors with a negligible failure probability. Finding codes with these properties is also motivated by Gottes...
Min-Max decoding for non binary LDPC codes
Savin, Valentin
2008-01-01
Iterative decoding of non-binary LDPC codes is currently performed using either the Sum-Product or the Min-Sum algorithms or slightly different versions of them. In this paper, several low-complexity quasi-optimal iterative algorithms are proposed for decoding non-binary codes. The Min-Max algorithm is one of them and it has the benefit of two possible LLR domain implementations: a standard implementation, whose complexity scales as the square of the Galois field's cardinality and a reduced c...
Decoding ensemble activity from neurophysiological recordings in the temporal cortex.
Kreiman, Gabriel
2011-01-01
We study subjects with pharmacologically intractable epilepsy who undergo semi-chronic implantation of electrodes for clinical purposes. We record physiological activity from tens to more than one hundred electrodes implanted in different parts of neocortex. These recordings provide higher spatial and temporal resolution than non-invasive measures of human brain activity. Here we discuss our efforts to develop hardware and algorithms to interact with the human brain by decoding ensemble activity in single trials. We focus our discussion on decoding visual information during a variety of visual object recognition tasks but the same technologies and algorithms can also be directly applied to other cognitive phenomena.
Linear-time general decoding algorithm for the surface code
Darmawan, Andrew S.; Poulin, David
2018-05-01
A quantum error correcting protocol can be substantially improved by taking into account features of the physical noise process. We present an efficient decoder for the surface code which can account for general noise features, including coherences and correlations. We demonstrate that the decoder significantly outperforms the conventional matching algorithm on a variety of noise models, including non-Pauli noise and spatially correlated noise. The algorithm is based on an approximate calculation of the logical channel using a tensor-network description of the noisy state.
Directory of Open Access Journals (Sweden)
David G. Daut
2007-03-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Directory of Open Access Journals (Sweden)
Liu Weiliang
2007-01-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel
Abediseid, Walid; Alouini, Mohamed-Slim
2013-01-01
channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement
Construction and decoding of matrix-product codes from nested codes
DEFF Research Database (Denmark)
Hernando, Fernando; Lally, Kristine; Ruano, Diego
2009-01-01
We consider matrix-product codes [C1 ... Cs] · A, where C1, ..., Cs are nested linear codes and matrix A has full rank. We compute their minimum distance and provide a decoding algorithm when A is a non-singular by columns matrix. The decoding algorithm decodes up to half of the minimum distance....
Adaptive decoding of MPEG-4 sprites for memory-constrained embedded systems
Pastrnak, M.; Farin, D.S.; With, de P.H.N.; Cardinal, J.; Cerf, N.; Delgrnage, O.
2005-01-01
Background sprite decoding is an essential part of object-based video coding.The composition and rendering of a final scene involves the placing of individual video objects in a predefined way superimposed on the decoded background image. The MPEG-4 standard includes the decoding algorithm for
Decoding sound level in the marmoset primary auditory cortex.
Sun, Wensheng; Marongelli, Ellisha N; Watkins, Paul V; Barbour, Dennis L
2017-10-01
Neurons that respond favorably to a particular sound level have been observed throughout the central auditory system, becoming steadily more common at higher processing areas. One theory about the role of these level-tuned or nonmonotonic neurons is the level-invariant encoding of sounds. To investigate this theory, we simulated various subpopulations of neurons by drawing from real primary auditory cortex (A1) neuron responses and surveyed their performance in forming different sound level representations. Pure nonmonotonic subpopulations did not provide the best level-invariant decoding; instead, mixtures of monotonic and nonmonotonic neurons provided the most accurate decoding. For level-fidelity decoding, the inclusion of nonmonotonic neurons slightly improved or did not change decoding accuracy until they constituted a high proportion. These results indicate that nonmonotonic neurons fill an encoding role complementary to, rather than alternate to, monotonic neurons. NEW & NOTEWORTHY Neurons with nonmonotonic rate-level functions are unique to the central auditory system. These level-tuned neurons have been proposed to account for invariant sound perception across sound levels. Through systematic simulations based on real neuron responses, this study shows that neuron populations perform sound encoding optimally when containing both monotonic and nonmonotonic neurons. The results indicate that instead of working independently, nonmonotonic neurons complement the function of monotonic neurons in different sound-encoding contexts. Copyright © 2017 the American Physiological Society.
Complete ML Decoding orf the (73,45) PG Code
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom; Hjaltason, Johan
2005-01-01
Our recent proof of the completeness of decoding by list bit flipping is reviewed. The proof is based on an enumeration of all cosets of low weight in terms of their minimum weight and syndrome weight. By using a geometric description of the error patterns we characterize all remaining cosets....
Decoding Representations: How Children with Autism Understand Drawings
Allen, Melissa L.
2009-01-01
Young typically developing children can reason about abstract depictions if they know the intention of the artist. Children with autism spectrum disorder (ASD), who are notably impaired in social, "intention monitoring" domains, may have great difficulty in decoding vague representations. In Experiment 1, children with ASD are unable to use…
A quantum algorithm for Viterbi decoding of classical convolutional codes
Grice, Jon R.; Meyer, David A.
2015-07-01
We present a quantum Viterbi algorithm (QVA) with better than classical performance under certain conditions. In this paper, the proposed algorithm is applied to decoding classical convolutional codes, for instance, large constraint length and short decode frames . Other applications of the classical Viterbi algorithm where is large (e.g., speech processing) could experience significant speedup with the QVA. The QVA exploits the fact that the decoding trellis is similar to the butterfly diagram of the fast Fourier transform, with its corresponding fast quantum algorithm. The tensor-product structure of the butterfly diagram corresponds to a quantum superposition that we show can be efficiently prepared. The quantum speedup is possible because the performance of the QVA depends on the fanout (number of possible transitions from any given state in the hidden Markov model) which is in general much less than . The QVA constructs a superposition of states which correspond to all legal paths through the decoding lattice, with phase as a function of the probability of the path being taken given received data. A specialized amplitude amplification procedure is applied one or more times to recover a superposition where the most probable path has a high probability of being measured.
The Fluid Reading Primer: Animated Decoding Support for Emergent Readers.
Zellweger, Polle T.; Mackinlay, Jock D.
A prototype application called the Fluid Reading Primer was developed to help emergent readers with the process of decoding written words into their spoken forms. The Fluid Reading Primer is part of a larger research project called Fluid Documents, which is exploring the use of interactive animation of typography to show additional information in…
Adaptive Combined Source and Channel Decoding with Modulation ...
African Journals Online (AJOL)
In this paper, an adaptive system employing combined source and channel decoding with modulation is proposed for slow Rayleigh fading channels. Huffman code is used as the source code and Convolutional code is used for error control. The adaptive scheme employs a family of Convolutional codes of different rates ...
Tracking Perceptual and Memory Decisions by Decoding Brain Activity
van Vugt, Marieke; Brandt, Armin; Schulze-Bonhage, Andreas
2017-01-01
Decision making is thought to involve a process of evidence accumulation, modelled as a drifting diffusion process. This modeling framework suggests that all single-stage decisions involve a similar evidence accumulation process. In this paper we use decoding by machine learning classifiers on
Peeling Decoding of LDPC Codes with Applications in Compressed Sensing
Directory of Open Access Journals (Sweden)
Weijun Zeng
2016-01-01
Full Text Available We present a new approach for the analysis of iterative peeling decoding recovery algorithms in the context of Low-Density Parity-Check (LDPC codes and compressed sensing. The iterative recovery algorithm is particularly interesting for its low measurement cost and low computational complexity. The asymptotic analysis can track the evolution of the fraction of unrecovered signal elements in each iteration, which is similar to the well-known density evolution analysis in the context of LDPC decoding algorithm. Our analysis shows that there exists a threshold on the density factor; if under this threshold, the recovery algorithm is successful; otherwise it will fail. Simulation results are also provided for verifying the agreement between the proposed asymptotic analysis and recovery algorithm. Compared with existing works of peeling decoding algorithm, focusing on the failure probability of the recovery algorithm, our proposed approach gives accurate evolution of performance with different parameters of measurement matrices and is easy to implement. We also show that the peeling decoding algorithm performs better than other schemes based on LDPC codes.
High-throughput GPU-based LDPC decoding
Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin
2010-08-01
Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.
Real Time Decoding of Color Symbol for Optical Positioning System
Directory of Open Access Journals (Sweden)
Abdul Waheed Malik
2015-01-01
Full Text Available This paper presents the design and real-time decoding of a color symbol that can be used as a reference marker for optical navigation. The designed symbol has a circular shape and is printed on paper using two distinct colors. This pair of colors is selected based on the highest achievable signal to noise ratio. The symbol is designed to carry eight bit information. Real time decoding of this symbol is performed using a heterogeneous combination of Field Programmable Gate Array (FPGA and a microcontroller. An image sensor having a resolution of 1600 by 1200 pixels is used to capture images of symbols in complex backgrounds. Dynamic image segmentation, component labeling and feature extraction was performed on the FPGA. The region of interest was further computed from the extracted features. Feature data belonging to the symbol was sent from the FPGA to the microcontroller. Image processing tasks are partitioned between the FPGA and microcontroller based on data intensity. Experiments were performed to verify the rotational independence of the symbols. The maximum distance between camera and symbol allowing for correct detection and decoding was analyzed. Experiments were also performed to analyze the number of generated image components and sub-pixel precision versus different light sources and intensities. The proposed hardware architecture can process up to 55 frames per second for accurate detection and decoding of symbols at two Megapixels resolution. The power consumption of the complete system is 342mw.
Fast decoding of codes from algebraic plane curves
DEFF Research Database (Denmark)
Justesen, Jørn; Larsen, Knud J.; Jensen, Helge Elbrønd
1992-01-01
Improvement to an earlier decoding algorithm for codes from algebraic geometry is presented. For codes from an arbitrary regular plane curve the authors correct up to d*/2-m2 /8+m/4-9/8 errors, where d* is the designed distance of the code and m is the degree of the curve. The complexity of finding...
Name that tune: decoding music from the listening brain.
Schaefer, R.S.; Farquhar, J.D.R.; Blokland, Y.M.; Sadakata, M.; Desain, P.W.M.
2011-01-01
In the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven
Name that tune: Decoding music from the listening brain
Schaefer, R.S.; Farquhar, J.D.R.; Blokland, Y.M.; Sadakata, M.; Desain, P.W.M.
2011-01-01
In the current study we use electroencephalography (EEG) to detect heard music from the brain signal, hypothesizing that the time structure in music makes it especially suitable for decoding perception from EEG signals. While excluding music with vocals, we classified the perception of seven
Decoding English Alphabet Letters Using EEG Phase Information
Directory of Open Access Journals (Sweden)
YiYan Wang
2018-02-01
Full Text Available Increasing evidence indicates that the phase pattern and power of the low frequency oscillations of brain electroencephalograms (EEG contain significant information during the human cognition of sensory signals such as auditory and visual stimuli. Here, we investigate whether and how the letters of the alphabet can be directly decoded from EEG phase and power data. In addition, we investigate how different band oscillations contribute to the classification and determine the critical time periods. An English letter recognition task was assigned, and statistical analyses were conducted to decode the EEG signal corresponding to each letter visualized on a computer screen. We applied support vector machine (SVM with gradient descent method to learn the potential features for classification. It was observed that the EEG phase signals have a higher decoding accuracy than the oscillation power information. Low-frequency theta and alpha oscillations have phase information with higher accuracy than do other bands. The decoding performance was best when the analysis period began from 180 to 380 ms after stimulus presentation, especially in the lateral occipital and posterior temporal scalp regions (PO7 and PO8. These results may provide a new approach for brain-computer interface techniques (BCI and may deepen our understanding of EEG oscillations in cognition.
O2-GIDNC: Beyond instantly decodable network coding
Aboutorab, Neda; Sorour, Sameh; Sadeghi, Parastoo
2013-01-01
In this paper, we are concerned with extending the graph representation of generalized instantly decodable network coding (GIDNC) to a more general opportunistic network coding (ONC) scenario, referred to as order-2 GIDNC (O2-GIDNC). In the O2-GIDNC
EEG source imaging assists decoding in a face recognition task
DEFF Research Database (Denmark)
Andersen, Rasmus S.; Eliasen, Anders U.; Pedersen, Nicolai
2017-01-01
of face recognition. This task concerns the differentiation of brain responses to images of faces and scrambled faces and poses a rather difficult decoding problem at the single trial level. We implement the pipeline using spatially focused features and show that this approach is challenged and source...
LDPC-based iterative joint source-channel decoding for JPEG2000.
Pu, Lingling; Wu, Zhenyu; Bilgin, Ali; Marcellin, Michael W; Vasic, Bane
2007-02-01
A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.
On Lattice Sequential Decoding for Large MIMO Systems
Ali, Konpal S.
2014-04-01
Due to their ability to provide high data rates, Multiple-Input Multiple-Output (MIMO) wireless communication systems have become increasingly popular. Decoding of these systems with acceptable error performance is computationally very demanding. In the case of large overdetermined MIMO systems, we employ the Sequential Decoder using the Fano Algorithm. A parameter called the bias is varied to attain different performance-complexity trade-offs. Low values of the bias result in excellent performance but at the expense of high complexity and vice versa for higher bias values. We attempt to bound the error by bounding the bias, using the minimum distance of a lattice. Also, a particular trend is observed with increasing SNR: a region of low complexity and high error, followed by a region of high complexity and error falling, and finally a region of low complexity and low error. For lower bias values, the stages of the trend are incurred at lower SNR than for higher bias values. This has the important implication that a low enough bias value, at low to moderate SNR, can result in low error and low complexity even for large MIMO systems. Our work is compared against Lattice Reduction (LR) aided Linear Decoders (LDs). Another impressive observation for low bias values that satisfy the error bound is that the Sequential Decoder\\'s error is seen to fall with increasing system size, while it grows for the LR-aided LDs. For the case of large underdetermined MIMO systems, Sequential Decoding with two preprocessing schemes is proposed – 1) Minimum Mean Square Error Generalized Decision Feedback Equalization (MMSE-GDFE) preprocessing 2) MMSE-GDFE preprocessing, followed by Lattice Reduction and Greedy Ordering. Our work is compared against previous work which employs Sphere Decoding preprocessed using MMSE-GDFE, Lattice Reduction and Greedy Ordering. For the case of large systems, this results in high complexity and difficulty in choosing the sphere radius. Our schemes
Multi-stage decoding for multi-level block modulation codes
Lin, Shu
1991-01-01
In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.
Real-time SHVC software decoding with multi-threaded parallel processing
Gudumasu, Srinivas; He, Yuwen; Ye, Yan; He, Yong; Ryu, Eun-Seok; Dong, Jie; Xiu, Xiaoyu
2014-09-01
This paper proposes a parallel decoding framework for scalable HEVC (SHVC). Various optimization technologies are implemented on the basis of SHVC reference software SHM-2.0 to achieve real-time decoding speed for the two layer spatial scalability configuration. SHVC decoder complexity is analyzed with profiling information. The decoding process at each layer and the up-sampling process are designed in parallel and scheduled by a high level application task manager. Within each layer, multi-threaded decoding is applied to accelerate the layer decoding speed. Entropy decoding, reconstruction, and in-loop processing are pipeline designed with multiple threads based on groups of coding tree units (CTU). A group of CTUs is treated as a processing unit in each pipeline stage to achieve a better trade-off between parallelism and synchronization. Motion compensation, inverse quantization, and inverse transform modules are further optimized with SSE4 SIMD instructions. Simulations on a desktop with an Intel i7 processor 2600 running at 3.4 GHz show that the parallel SHVC software decoder is able to decode 1080p spatial 2x at up to 60 fps (frames per second) and 1080p spatial 1.5x at up to 50 fps for those bitstreams generated with SHVC common test conditions in the JCT-VC standardization group. The decoding performance at various bitrates with different optimization technologies and different numbers of threads are compared in terms of decoding speed and resource usage, including processor and memory.
Decoding bipedal locomotion from the rat sensorimotor cortex
Rigosa, J.; Panarese, A.; Dominici, N.; Friedli, L.; van den Brand, R.; Carpaneto, J.; DiGiovanna, J.; Courtine, G.; Micera, S.
2015-10-01
Objective. Decoding forelimb movements from the firing activity of cortical neurons has been interfaced with robotic and prosthetic systems to replace lost upper limb functions in humans. Despite the potential of this approach to improve locomotion and facilitate gait rehabilitation, decoding lower limb movement from the motor cortex has received comparatively little attention. Here, we performed experiments to identify the type and amount of information that can be decoded from neuronal ensemble activity in the hindlimb area of the rat motor cortex during bipedal locomotor tasks. Approach. Rats were trained to stand, step on a treadmill, walk overground and climb staircases in a bipedal posture. To impose this gait, the rats were secured in a robotic interface that provided support against the direction of gravity and in the mediolateral direction, but behaved transparently in the forward direction. After completion of training, rats were chronically implanted with a micro-wire array spanning the left hindlimb motor cortex to record single and multi-unit activity, and bipolar electrodes into 10 muscles of the right hindlimb to monitor electromyographic signals. Whole-body kinematics, muscle activity, and neural signals were simultaneously recorded during execution of the trained tasks over multiple days of testing. Hindlimb kinematics, muscle activity, gait phases, and locomotor tasks were decoded using offline classification algorithms. Main results. We found that the stance and swing phases of gait and the locomotor tasks were detected with accuracies as robust as 90% in all rats. Decoded hindlimb kinematics and muscle activity exhibited a larger variability across rats and tasks. Significance. Our study shows that the rodent motor cortex contains useful information for lower limb neuroprosthetic development. However, brain-machine interfaces estimating gait phases or locomotor behaviors, instead of continuous variables such as limb joint positions or speeds
Low Complexity Approach for High Throughput Belief-Propagation based Decoding of LDPC Codes
Directory of Open Access Journals (Sweden)
BOT, A.
2013-11-01
Full Text Available The paper proposes a low complexity belief propagation (BP based decoding algorithm for LDPC codes. In spite of the iterative nature of the decoding process, the proposed algorithm provides both reduced complexity and increased BER performances as compared with the classic min-sum (MS algorithm, generally used for hardware implementations. Linear approximations of check-nodes update function are used in order to reduce the complexity of the BP algorithm. Considering this decoding approach, an FPGA based hardware architecture is proposed for implementing the decoding algorithm, aiming to increase the decoder throughput. FPGA technology was chosen for the LDPC decoder implementation, due to its parallel computation and reconfiguration capabilities. The obtained results show improvements regarding decoding throughput and BER performances compared with state-of-the-art approaches.
Low Power LDPC Code Decoder Architecture Based on Intermediate Message Compression Technique
Shimizu, Kazunori; Togawa, Nozomu; Ikenaga, Takeshi; Goto, Satoshi
Reducing the power dissipation for LDPC code decoder is a major challenging task to apply it to the practical digital communication systems. In this paper, we propose a low power LDPC code decoder architecture based on an intermediate message-compression technique which features as follows: (i) An intermediate message compression technique enables the decoder to reduce the required memory capacity and write power dissipation. (ii) A clock gated shift register based intermediate message memory architecture enables the decoder to decompress the compressed messages in a single clock cycle while reducing the read power dissipation. The combination of the above two techniques enables the decoder to reduce the power dissipation while keeping the decoding throughput. The simulation results show that the proposed architecture improves the power efficiency up to 52% and 18% compared to that of the decoder based on the overlapped schedule and the rapid convergence schedule without the proposed techniques respectively.
Design of FBG En/decoders in Coherent 2-D Time-polarization OCDMA Systems
Hou, Fen-fei; Yang, Ming
2012-12-01
A novel fiber Bragg grating (FBG)-based en/decoder for the two-dimensional (2-D) time-spreading and polarization multiplexer optical coding is proposed. Compared with other 2-D en/decoders, the proposed en/decoding for an optical code-division multiple-access (OCDMA) system uses a single phase-encoded FBG and coherent en/decoding. Furthermore, combined with reconstruction-equivalent-chirp technology, such en/decoders can be realized with a conventional simple fabrication setup. Experimental results of such en/decoders and the corresponding system test at a data rate of 5 Gbit/s demonstrate that this kind of 2-D FBG-based en/decoders could improve the performances of OCDMA systems.
Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.
Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup
2011-09-01
The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.
Performance-complexity tradeoff in sequential decoding for the unconstrained AWGN channel
Abediseid, Walid
2013-06-01
In this paper, the performance limits and the computational complexity of the lattice sequential decoder are analyzed for the unconstrained additive white Gaussian noise channel. The performance analysis available in the literature for such a channel has been studied only under the use of the minimum Euclidean distance decoder that is commonly referred to as the lattice decoder. Lattice decoders based on solutions to the NP-hard closest vector problem are very complex to implement, and the search for low complexity receivers for the detection of lattice codes is considered a challenging problem. However, the low computational complexity advantage that sequential decoding promises, makes it an alternative solution to the lattice decoder. In this work, we characterize the performance and complexity tradeoff via the error exponent and the decoding complexity, respectively, of such a decoder as a function of the decoding parameter - the bias term. For the above channel, we derive the cut-off volume-to-noise ratio that is required to achieve a good error performance with low decoding complexity. © 2013 IEEE.
Sheikh, Alireza; Amat, Alexandre Graell i.; Liva, Gianluigi
2017-12-01
We analyze the achievable information rates (AIRs) for coded modulation schemes with QAM constellations with both bit-wise and symbol-wise decoders, corresponding to the case where a binary code is used in combination with a higher-order modulation using the bit-interleaved coded modulation (BICM) paradigm and to the case where a nonbinary code over a field matched to the constellation size is used, respectively. In particular, we consider hard decision decoding, which is the preferable option for fiber-optic communication systems where decoding complexity is a concern. Recently, Liga \\emph{et al.} analyzed the AIRs for bit-wise and symbol-wise decoders considering what the authors called \\emph{hard decision decoder} which, however, exploits \\emph{soft information} of the transition probabilities of discrete-input discrete-output channel resulting from the hard detection. As such, the complexity of the decoder is essentially the same as the complexity of a soft decision decoder. In this paper, we analyze instead the AIRs for the standard hard decision decoder, commonly used in practice, where the decoding is based on the Hamming distance metric. We show that if standard hard decision decoding is used, bit-wise decoders yield significantly higher AIRs than symbol-wise decoders. As a result, contrary to the conclusion by Liga \\emph{et al.}, binary decoders together with the BICM paradigm are preferable for spectrally-efficient fiber-optic systems. We also design binary and nonbinary staircase codes and show that, in agreement with the AIRs, binary codes yield better performance.
STACK DECODING OF LINEAR BLOCK CODES FOR DISCRETE MEMORYLESS CHANNEL USING TREE DIAGRAM
Directory of Open Access Journals (Sweden)
H. Prashantha Kumar
2012-03-01
Full Text Available The boundaries between block and convolutional codes have become diffused after recent advances in the understanding of the trellis structure of block codes and the tail-biting structure of some convolutional codes. Therefore, decoding algorithms traditionally proposed for decoding convolutional codes have been applied for decoding certain classes of block codes. This paper presents the decoding of block codes using tree structure. Many good block codes are presently known. Several of them have been used in applications ranging from deep space communication to error control in storage systems. But the primary difficulty with applying Viterbi or BCJR algorithms to decode of block codes is that, even though they are optimum decoding methods, the promised bit error rates are not achieved in practice at data rates close to capacity. This is because the decoding effort is fixed and grows with block length, and thus only short block length codes can be used. Therefore, an important practical question is whether a suboptimal realizable soft decision decoding method can be found for block codes. A noteworthy result which provides a partial answer to this question is described in the following sections. This result of near optimum decoding will be used as motivation for the investigation of different soft decision decoding methods for linear block codes which can lead to the development of efficient decoding algorithms. The code tree can be treated as an expanded version of the trellis, where every path is totally distinct from every other path. We have derived the tree structure for (8, 4 and (16, 11 extended Hamming codes and have succeeded in implementing the soft decision stack algorithm to decode them. For the discrete memoryless channel, gains in excess of 1.5dB at a bit error rate of 10-5 with respect to conventional hard decision decoding are demonstrated for these codes.
Decoding thalamic afferent input using microcircuit spiking activity.
Sederberg, Audrey J; Palmer, Stephanie E; MacLean, Jason N
2015-04-01
A behavioral response appropriate to a sensory stimulus depends on the collective activity of thousands of interconnected neurons. The majority of cortical connections arise from neighboring neurons, and thus understanding the cortical code requires characterizing information representation at the scale of the cortical microcircuit. Using two-photon calcium imaging, we densely sampled the thalamically evoked response of hundreds of neurons spanning multiple layers and columns in thalamocortical slices of mouse somatosensory cortex. We then used a biologically plausible decoder to characterize the representation of two distinct thalamic inputs, at the level of the microcircuit, to reveal those aspects of the activity pattern that are likely relevant to downstream neurons. Our data suggest a sparse code, distributed across lamina, in which a small population of cells carries stimulus-relevant information. Furthermore, we find that, within this subset of neurons, decoder performance improves when noise correlations are taken into account. Copyright © 2015 the American Physiological Society.
Codes on the Klein quartic, ideals, and decoding
DEFF Research Database (Denmark)
Hansen, Johan P.
1987-01-01
descriptions as left ideals in the group-algebra GF(2^{3})[G]. This description allows for easy decoding. For instance, in the case of the single error correcting code of length21and dimension16with minimal distance3. decoding is obtained by multiplication with an idempotent in the group algebra.......A sequence of codes with particular symmetries and with large rates compared to their minimal distances is constructed over the field GF(2^{3}). In the sequence there is, for instance, a code of length 21 and dimension10with minimal distance9, and a code of length21and dimension16with minimal...... distance3. The codes are constructed from algebraic geometry using the dictionary between coding theory and algebraic curves over finite fields established by Goppa. The curve used in the present work is the Klein quartic. This curve has the maximal number of rational points over GF(2^{3})allowed by Serre...
Soft decoding a self-dual (48, 24; 12) code
Solomon, G.
1993-01-01
A self-dual (48,24;12) code comes from restricting a binary cyclic (63,18;36) code to a 6 x 7 matrix, adding an eighth all-zero column, and then adjoining six dimensions to this extended 6 x 8 matrix. These six dimensions are generated by linear combinations of row permutations of a 6 x 8 matrix of weight 12, whose sums of rows and columns add to one. A soft decoding using these properties and approximating maximum likelihood is presented here. This is preliminary to a possible soft decoding of the box (72,36;15) code that promises a 7.7-dB theoretical coding under maximum likelihood.
DECODING OF ACADEMIC CONTENT BY THE 1st GRADE STUDENTS
Directory of Open Access Journals (Sweden)
Kamil Błaszczyński
2017-07-01
Full Text Available In the paper a comparative study conducted on the 1st grade students of sociology and pedagogy is discussed. The study was focused on the language skills of students. The most important skills tested were the abilities to decode academic content. The study shows that the students have very poor language skills in decoding the academic content on every level of its complexity. They also have noticeable problems with the definition of basic academic terms. The significance of the obtained results are high because of the innovative topic and character of the study, which was the first such study conducted on students of a Polish university. Results are also valuable for academic teachers who are interested in such problems as effective communication with students.
Decoding Signal Processing at the Single-Cell Level
Energy Technology Data Exchange (ETDEWEB)
Wiley, H. Steven
2017-12-01
The ability of cells to detect and decode information about their extracellular environment is critical to generating an appropriate response. In multicellular organisms, cells must decode dozens of signals from their neighbors and extracellular matrix to maintain tissue homeostasis while still responding to environmental stressors. How cells detect and process information from their surroundings through a surprisingly limited number of signal transduction pathways is one of the most important question in biology. Despite many decades of research, many of the fundamental principles that underlie cell signal processing remain obscure. However, in this issue of Cell Systems, Gillies et al present compelling evidence that the early response gene circuit can act as a linear signal integrator, thus providing significant insight into how cells handle fluctuating signals and noise in their environment.
Reaction Decoder Tool (RDT): extracting features from chemical reactions.
Rahman, Syed Asad; Torrance, Gilliean; Baldacci, Lorenzo; Martínez Cuesta, Sergio; Fenninger, Franz; Gopal, Nimish; Choudhary, Saket; May, John W; Holliday, Gemma L; Steinbeck, Christoph; Thornton, Janet M
2016-07-01
Extracting chemical features like Atom-Atom Mapping (AAM), Bond Changes (BCs) and Reaction Centres from biochemical reactions helps us understand the chemical composition of enzymatic reactions. Reaction Decoder is a robust command line tool, which performs this task with high accuracy. It supports standard chemical input/output exchange formats i.e. RXN/SMILES, computes AAM, highlights BCs and creates images of the mapped reaction. This aids in the analysis of metabolic pathways and the ability to perform comparative studies of chemical reactions based on these features. This software is implemented in Java, supported on Windows, Linux and Mac OSX, and freely available at https://github.com/asad/ReactionDecoder : asad@ebi.ac.uk or s9asad@gmail.com. © The Author 2016. Published by Oxford University Press.
Fast decoder for local quantum codes using Groebner basis
Haah, Jeongwan
2013-03-01
Based on arXiv:1204.1063. A local translation-invariant quantum code has a description in terms of Laurent polynomials. As an application of this observation, we present a fast decoding algorithm for translation-invariant local quantum codes in any spatial dimensions using the straightforward division algorithm for multivariate polynomials. The running time is O (n log n) on average, or O (n2 log n) on worst cases, where n is the number of physical qubits. The algorithm improves a subroutine of the renormalization-group decoder by Bravyi and Haah (arXiv:1112.3252) in the translation-invariant case. This work is supported in part by the Insitute for Quantum Information and Matter, an NSF Physics Frontier Center, and the Korea Foundation for Advanced Studies.
[Efficacy of decoding training for children with difficulty reading hiragana].
Uchiyama, Hitoshi; Tanaka, Daisuke; Seki, Ayumi; Wakamiya, Eiji; Hirasawa, Noriko; Iketani, Naotake; Kato, Ken; Koeda, Tatsuya
2013-05-01
The present study aimed to clarify the efficacy of decoding training focusing on the correspondence between written symbols and their readings for children with difficulty reading hiragana (Japanese syllabary). Thirty-five children with difficulty reading hiragana were selected from among 367 first-grade elementary school students using a reading aloud test and were then divided into intervention (n=15) and control (n=20) groups. The intervention comprised 5 minutes of decoding training each day for a period of 3 weeks using an original program on a personal computer. Reading time and number of reading errors in the reading aloud test were compared between the groups. The intervention group showed a significant shortening of reading time (F(1,33)=5.40, phiragana.
Iterative demodulation and decoding of coded non-square QAM
Li, L.; Divsalar, D.; Dolinar, S.
2003-01-01
Simulation results show that, with iterative demodulation and decoding, coded NS-8QAM performs 0.5 dB better than standard 8QAM and 0.7 dB better than 8PSK at BER= 10(sup -5), when the FEC code is the (15, 11) Hamming code concatenated with a rate-1 accumulator code, while coded NS-32QAM performs 0.25 dB better than standard 32QAM.
Design and Implementation of Viterbi Decoder Using VHDL
Thakur, Akash; Chattopadhyay, Manju K.
2018-03-01
A digital design conversion of Viterbi decoder for ½ rate convolutional encoder with constraint length k = 3 is presented in this paper. The design is coded with the help of VHDL, simulated and synthesized using XILINX ISE 14.7. Synthesis results show a maximum frequency of operation for the design is 100.725 MHz. The requirement of memory is less as compared to conventional method.
Maximum likelihood convolutional decoding (MCD) performance due to system losses
Webster, L.
1976-01-01
A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.
Decoding Gimmicks of Financial Shenanigans in Telecom Sector in India
Sandeep GOEL
2013-01-01
Major corporate financial shenanigans get away in the name of creative accounting. But, they need to be studied for lessons learned and strategies to avoid or reduce the incidence of such frauds in the future. It is essential for shareholders, particularly the common man who does not have any access to the company except reported financial numbers. This paper aims to decode the level of financial shenanigans practices in corporate enterprises in telecom sector in India. The reason being is th...
Fast Transform Decoding Of Nonsystematic Reed-Solomon Codes
Truong, Trieu-Kie; Cheung, Kar-Ming; Shiozaki, A.; Reed, Irving S.
1992-01-01
Fast, efficient Fermat number transform used to compute F'(x) analogous to computation of syndrome in conventional decoding scheme. Eliminates polynomial multiplications and reduces number of multiplications in reconstruction of F'(x) to n log (n). Euclidean algorithm used to evaluate F(x) directly, without going through intermediate steps of solving error-locator and error-evaluator polynomials. Algorithm suitable for implementation in very-large-scale integrated circuits.
Efficient algorithms for maximum likelihood decoding in the surface code
Bravyi, Sergey; Suchara, Martin; Vargo, Alexander
2014-09-01
We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the two-dimensional surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time O (n2), where n is the number of code qubits. Our implementation uses a reduction from MLD to simulation of matchgate quantum circuits. This reduction however requires a special noise model with independent bit-flip and phase-flip errors. Secondly, we show how to implement MLD approximately for more general noise models using matrix product states (MPS). Our implementation has running time O (nχ3), where χ is a parameter that controls the approximation precision. The key step of our algorithm, borrowed from the density matrix renormalization-group method, is a subroutine for contracting a tensor network on the two-dimensional grid. The subroutine uses MPS with a bond dimension χ to approximate the sequence of tensors arising in the course of contraction. We benchmark the MPS-based decoder against the standard minimum weight matching decoder observing a significant reduction of the logical error probability for χ ≥4.
Biological 2-Input Decoder Circuit in Human Cells
2015-01-01
Decoders are combinational circuits that convert information from n inputs to a maximum of 2n outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions. PMID:24694115
An Area-Efficient Reconfigurable LDPC Decoder with Conflict Resolution
Zhou, Changsheng; Huang, Yuebin; Huang, Shuangqu; Chen, Yun; Zeng, Xiaoyang
Based on Turbo-Decoding Message-Passing (TDMP) and Normalized Min-Sum (NMS) algorithm, an area efficient LDPC decoder that supports both structured and unstructured LDPC codes is proposed in this paper. We introduce a solution to solve the memory access conflict problem caused by TDMP algorithm. We also arrange the main timing schedule carefully to handle the operations of our solution while avoiding much additional hardware consumption. To reduce the memory bits needed, the extrinsic message storing strategy is also optimized. Besides the extrinsic message recover and the accumulate operation are merged together. To verify our architecture, a LDPC decoder that supports both China Multimedia Mobile Broadcasting (CMMB) and Digital Terrestrial/ Television Multimedia Broadcasting (DTMB) standards is developed using SMIC 0.13µm standard CMOS process. The core area is 4.75mm2 and the maximum operating clock frequency is 200MHz. The estimated power consumption is 48.4mW at 25MHz for CMMB and 130.9mW at 50MHz for DTMB with 5 iterations and 1.2V supply.
Biological 2-input decoder circuit in human cells.
Guinn, Michael; Bleris, Leonidas
2014-08-15
Decoders are combinational circuits that convert information from n inputs to a maximum of 2(n) outputs. This operation is of major importance in computing systems yet it is vastly underexplored in synthetic biology. Here, we present a synthetic gene network architecture that operates as a biological decoder in human cells, converting 2 inputs to 4 outputs. As a proof-of-principle, we use small molecules to emulate the two inputs and fluorescent reporters as the corresponding four outputs. The experiments are performed using transient transfections in human kidney embryonic cells and the characterization by fluorescence microscopy and flow cytometry. We show a clear separation between the ON and OFF mean fluorescent intensity states. Additionally, we adopt the integrated mean fluorescence intensity for the characterization of the circuit and show that this metric is more robust to transfection conditions when compared to the mean fluorescent intensity. To conclude, we present the first implementation of a genetic decoder. This combinational system can be valuable toward engineering higher-order circuits as well as accommodate a multiplexed interface with endogenous cellular functions.
The basis of orientation decoding in human primary visual cortex: fine- or coarse-scale biases?
Maloney, Ryan T
2015-01-01
Orientation signals in human primary visual cortex (V1) can be reliably decoded from the multivariate pattern of activity as measured with functional magnetic resonance imaging (fMRI). The precise underlying source of these decoded signals (whether by orientation biases at a fine or coarse scale in cortex) remains a matter of some controversy, however. Freeman and colleagues (J Neurosci 33: 19695-19703, 2013) recently showed that the accuracy of decoding of spiral patterns in V1 can be predicted by a voxel's preferred spatial position (the population receptive field) and its coarse orientation preference, suggesting that coarse-scale biases are sufficient for orientation decoding. Whether they are also necessary for decoding remains an open question, and one with implications for the broader interpretation of multivariate decoding results in fMRI studies. Copyright © 2015 the American Physiological Society.
Emotion Decoding and Incidental Processing Fluency as Antecedents of Attitude Certainty.
Petrocelli, John V; Whitmire, Melanie B
2017-07-01
Previous research demonstrates that attitude certainty influences the degree to which an attitude changes in response to persuasive appeals. In the current research, decoding emotions from facial expressions and incidental processing fluency, during attitude formation, are examined as antecedents of both attitude certainty and attitude change. In Experiment 1, participants who decoded anger or happiness during attitude formation expressed their greater attitude certainty, and showed more resistance to persuasion than participants who decoded sadness. By manipulating the emotion decoded, the diagnosticity of processing fluency experienced during emotion decoding, and the gaze direction of the social targets, Experiment 2 suggests that the link between emotion decoding and attitude certainty results from incidental processing fluency. Experiment 3 demonstrated that fluency in processing irrelevant stimuli influences attitude certainty, which in turn influences resistance to persuasion. Implications for appraisal-based accounts of attitude formation and attitude change are discussed.
Coding/decoding two-dimensional images with orbital angular momentum of light.
Chu, Jiaqi; Li, Xuefeng; Smithwick, Quinn; Chu, Daping
2016-04-01
We investigate encoding and decoding of two-dimensional information using the orbital angular momentum (OAM) of light. Spiral phase plates and phase-only spatial light modulators are used in encoding and decoding of OAM states, respectively. We show that off-axis points and spatial variables encoded with a given OAM state can be recovered through decoding with the corresponding complimentary OAM state.
A Low-Complexity Joint Detection-Decoding Algorithm for Nonbinary LDPC-Coded Modulation Systems
Wang, Xuepeng; Bai, Baoming; Ma, Xiao
2010-01-01
In this paper, we present a low-complexity joint detection-decoding algorithm for nonbinary LDPC codedmodulation systems. The algorithm combines hard-decision decoding using the message-passing strategy with the signal detector in an iterative manner. It requires low computational complexity, offers good system performance and has a fast rate of decoding convergence. Compared to the q-ary sum-product algorithm (QSPA), it provides an attractive candidate for practical applications of q-ary LDP...
Decoding using back-project algorithm from coded image in ICF
International Nuclear Information System (INIS)
Jiang shaoen; Liu Zhongli; Zheng Zhijian; Tang Daoyuan
1999-01-01
The principle of the coded imaging and its decoding in inertial confinement fusion is described simply. The authors take ring aperture microscope for example and use back-project (BP) algorithm to decode the coded image. The decoding program has been performed for numerical simulation. Simulations of two models are made, and the results show that the accuracy of BP algorithm is high and effect of reconstruction is good. Thus, it indicates that BP algorithm is applicable to decoding for coded image in ICF experiments
Analysis of Iterated Hard Decision Decoding of Product Codes with Reed-Solomon Component Codes
DEFF Research Database (Denmark)
Justesen, Jørn; Høholdt, Tom
2007-01-01
Products of Reed-Solomon codes are important in applications because they offer a combination of large blocks, low decoding complexity, and good performance. A recent result on random graphs can be used to show that with high probability a large number of errors can be corrected by iterating...... minimum distance decoding. We present an analysis related to density evolution which gives the exact asymptotic value of the decoding threshold and also provides a closed form approximation to the distribution of errors in each step of the decoding of finite length codes....
VLSI Architectures for Sliding-Window-Based Space-Time Turbo Trellis Code Decoders
Directory of Open Access Journals (Sweden)
Georgios Passas
2012-01-01
Full Text Available The VLSI implementation of SISO-MAP decoders used for traditional iterative turbo coding has been investigated in the literature. In this paper, a complete architectural model of a space-time turbo code receiver that includes elementary decoders is presented. These architectures are based on newly proposed building blocks such as a recursive add-compare-select-offset (ACSO unit, A-, B-, Γ-, and LLR output calculation modules. Measurements of complexity and decoding delay of several sliding-window-technique-based MAP decoder architectures and a proposed parameter set lead to defining equations and comparison between those architectures.
A new LDPC decoding scheme for PDM-8QAM BICM coherent optical communication system
Liu, Yi; Zhang, Wen-bo; Xi, Li-xia; Tang, Xian-feng; Zhang, Xiao-guang
2015-11-01
A new log-likelihood ratio (LLR) message estimation method is proposed for polarization-division multiplexing eight quadrature amplitude modulation (PDM-8QAM) bit-interleaved coded modulation (BICM) optical communication system. The formulation of the posterior probability is theoretically analyzed, and the way to reduce the pre-decoding bit error rate ( BER) of the low density parity check (LDPC) decoder for PDM-8QAM constellations is presented. Simulation results show that it outperforms the traditional scheme, i.e., the new post-decoding BER is decreased down to 50% of that of the traditional post-decoding algorithm.
Multiple-Symbol Noncoherent Decoding of Uncoded and Convolutionally Codes Continous Phase Modulation
Divsalar, D.; Raphaeli, D.
2000-01-01
Recently, a method for combined noncoherent detection and decoding of trellis-codes (noncoherent coded modulation) has been proposed, which can practically approach the performance of coherent detection.
Firing rate estimation using infinite mixture models and its application to neural decoding.
Shibue, Ryohei; Komaki, Fumiyasu
2017-11-01
Neural decoding is a framework for reconstructing external stimuli from spike trains recorded by various neural recordings. Kloosterman et al. proposed a new decoding method using marked point processes (Kloosterman F, Layton SP, Chen Z, Wilson MA. J Neurophysiol 111: 217-227, 2014). This method does not require spike sorting and thereby improves decoding accuracy dramatically. In this method, they used kernel density estimation to estimate intensity functions of marked point processes. However, the use of kernel density estimation causes problems such as low decoding accuracy and high computational costs. To overcome these problems, we propose a new decoding method using infinite mixture models to estimate intensity. The proposed method improves decoding performance in terms of accuracy and computational speed. We apply the proposed method to simulation and experimental data to verify its performance. NEW & NOTEWORTHY We propose a new neural decoding method using infinite mixture models and nonparametric Bayesian statistics. The proposed method improves decoding performance in terms of accuracy and computation speed. We have successfully applied the proposed method to position decoding from spike trains recorded in a rat hippocampus. Copyright © 2017 the American Physiological Society.
Parallel iterative decoding of transform domain Wyner-Ziv video using cross bitplane correlation
DEFF Research Database (Denmark)
Luong, Huynh Van; Huang, Xin; Forchhammer, Søren
2011-01-01
decoding scheme is proposed to improve the coding efficiency of TDWZ video codecs. The proposed parallel iterative LDPC decoding scheme is able to utilize cross bitplane correlation during decoding, by iteratively refining the soft-input, updating a modeled noise distribution and thereafter enhancing......In recent years, Transform Domain Wyner-Ziv (TDWZ) video coding has been proposed as an efficient Distributed Video Coding (DVC) solution, which fully or partly exploits the source statistics at the decoder to reduce the computational burden at the encoder. In this paper, a parallel iterative LDPC...
Visual perception as retrospective Bayesian decoding from high- to low-level features.
Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning
2017-10-24
When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.
An Improved Unscented Kalman Filter Based Decoder for Cortical Brain-Machine Interfaces.
Li, Simin; Li, Jie; Li, Zheng
2016-01-01
Brain-machine interfaces (BMIs) seek to connect brains with machines or computers directly, for application in areas such as prosthesis control. For this application, the accuracy of the decoding of movement intentions is crucial. We aim to improve accuracy by designing a better encoding model of primary motor cortical activity during hand movements and combining this with decoder engineering refinements, resulting in a new unscented Kalman filter based decoder, UKF2, which improves upon our previous unscented Kalman filter decoder, UKF1. The new encoding model includes novel acceleration magnitude, position-velocity interaction, and target-cursor-distance features (the decoder does not require target position as input, it is decoded). We add a novel probabilistic velocity threshold to better determine the user's intent to move. We combine these improvements with several other refinements suggested by others in the field. Data from two Rhesus monkeys indicate that the UKF2 generates offline reconstructions of hand movements (mean CC 0.851) significantly more accurately than the UKF1 (0.833) and the popular position-velocity Kalman filter (0.812). The encoding model of the UKF2 could predict the instantaneous firing rate of neurons (mean CC 0.210), given kinematic variables and past spiking, better than the encoding models of these two decoders (UKF1: 0.138, p-v Kalman: 0.098). In closed-loop experiments where each monkey controlled a computer cursor with each decoder in turn, the UKF2 facilitated faster task completion (mean 1.56 s vs. 2.05 s) and higher Fitts's Law bit rate (mean 0.738 bit/s vs. 0.584 bit/s) than the UKF1. These results suggest that the modeling and decoder engineering refinements of the UKF2 improve decoding performance. We believe they can be used to enhance other decoders as well.
Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes
Lin, Shu
1998-01-01
A code trellis is a graphical representation of a code, block or convolutional, in which every path represents a codeword (or a code sequence for a convolutional code). This representation makes it possible to implement Maximum Likelihood Decoding (MLD) of a code with reduced decoding complexity. The most well known trellis-based MLD algorithm is the Viterbi algorithm. The trellis representation was first introduced and used for convolutional codes [23]. This representation, together with the Viterbi decoding algorithm, has resulted in a wide range of applications of convolutional codes for error control in digital communications over the last two decades. There are two major reasons for this inactive period of research in this area. First, most coding theorists at that time believed that block codes did not have simple trellis structure like convolutional codes and maximum likelihood decoding of linear block codes using the Viterbi algorithm was practically impossible, except for very short block codes. Second, since almost all of the linear block codes are constructed algebraically or based on finite geometries, it was the belief of many coding theorists that algebraic decoding was the only way to decode these codes. These two reasons seriously hindered the development of efficient soft-decision decoding methods for linear block codes and their applications to error control in digital communications. This led to a general belief that block codes are inferior to convolutional codes and hence, that they were not useful. Chapter 2 gives a brief review of linear block codes. The goal is to provide the essential background material for the development of trellis structure and trellis-based decoding algorithms for linear block codes in the later chapters. Chapters 3 through 6 present the fundamental concepts, finite-state machine model, state space formulation, basic structural properties, state labeling, construction procedures, complexity, minimality, and
Research on coding and decoding method for digital levels
Energy Technology Data Exchange (ETDEWEB)
Tu Lifen; Zhong Sidong
2011-01-20
A new coding and decoding method for digital levels is proposed. It is based on an area-array CCD sensor and adopts mixed coding technology. By taking advantage of redundant information in a digital image signal, the contradiction that the field of view and image resolution restrict each other in a digital level measurement is overcome, and the geodetic leveling becomes easier. The experimental results demonstrate that the uncertainty of measurement is 1mm when the measuring range is between 2m and 100m, which can meet practical needs.
Research on coding and decoding method for digital levels.
Tu, Li-fen; Zhong, Si-dong
2011-01-20
A new coding and decoding method for digital levels is proposed. It is based on an area-array CCD sensor and adopts mixed coding technology. By taking advantage of redundant information in a digital image signal, the contradiction that the field of view and image resolution restrict each other in a digital level measurement is overcome, and the geodetic leveling becomes easier. The experimental results demonstrate that the uncertainty of measurement is 1 mm when the measuring range is between 2 m and 100 m, which can meet practical needs.
Central Decoding for Multiple Description Codes based on Domain Partitioning
Directory of Open Access Journals (Sweden)
M. Spiertz
2006-01-01
Full Text Available Multiple Description Codes (MDC can be used to trade redundancy against packet loss resistance for transmitting data over lossy diversity networks. In this work we focus on MD transform coding based on domain partitioning. Compared to Vaishampayan’s quantizer based MDC, domain based MD coding is a simple approach for generating different descriptions, by using different quantizers for each description. Commonly, only the highest rate quantizer is used for reconstruction. In this paper we investigate the benefit of using the lower rate quantizers to enhance the reconstruction quality at decoder side. The comparison is done on artificial source data and on image data.
An LDPC decoder architecture for wireless sensor network applications.
Biroli, Andrea Dario Giancarlo; Martina, Maurizio; Masera, Guido
2012-01-01
The pervasive use of wireless sensors in a growing spectrum of human activities reinforces the need for devices with low energy dissipation. In this work, coded communication between a couple of wireless sensor devices is considered as a method to reduce the dissipated energy per transmitted bit with respect to uncoded communication. Different Low Density Parity Check (LDPC) codes are considered to this purpose and post layout results are shown for a low-area low-energy decoder, which offers percentage energy savings with respect to the uncoded solution in the range of 40%-80%, depending on considered environment, distance and bit error rate.
Optimized iterative decoding method for TPC coded CPM
Ma, Yanmin; Lai, Penghui; Wang, Shilian; Xie, Shunqin; Zhang, Wei
2018-05-01
Turbo Product Code (TPC) coded Continuous Phase Modulation (CPM) system (TPC-CPM) has been widely used in aeronautical telemetry and satellite communication. This paper mainly investigates the improvement and optimization on the TPC-CPM system. We first add the interleaver and deinterleaver to the TPC-CPM system, and then establish an iterative system to iteratively decode. However, the improved system has a poor convergence ability. To overcome this issue, we use the Extrinsic Information Transfer (EXIT) analysis to find the optimal factors for the system. The experiments show our method is efficient to improve the convergence performance.
Synthesizer for decoding a coded short wave length irradiation
International Nuclear Information System (INIS)
1976-01-01
The system uses point irradiation source, typically an X-ray emitter, which illuminates a three dimensional object consisting of a set of parallel planes, each of which acts as a source of coded information. The secondary source images are superimposed on a common flat screen. The decoding system comprises an imput light-screen detector, a picture screen amplifier, a beam deflector, on output picture screen, an optical focussing unit including three lenses, a masking unit, an output light screen detector and a video signal reproduction unit of cathode ray tube from, or similar, to create a three dimensional image of the object. (G.C.)
New decoding methods of interleaved burst error-correcting codes
Nakano, Y.; Kasahara, M.; Namekawa, T.
1983-04-01
A probabilistic method of single burst error correction, using the syndrome correlation of subcodes which constitute the interleaved code, is presented. This method makes it possible to realize a high capability of burst error correction with less decoding delay. By generalizing this method it is possible to obtain probabilistic method of multiple (m-fold) burst error correction. After estimating the burst error positions using syndrome correlation of subcodes which are interleaved m-fold burst error detecting codes, this second method corrects erasure errors in each subcode and m-fold burst errors. The performance of these two methods is analyzed via computer simulation, and their effectiveness is demonstrated.
An LDPC Decoder Architecture for Wireless Sensor Network Applications
Giancarlo Biroli, Andrea Dario; Martina, Maurizio; Masera, Guido
2012-01-01
The pervasive use of wireless sensors in a growing spectrum of human activities reinforces the need for devices with low energy dissipation. In this work, coded communication between a couple of wireless sensor devices is considered as a method to reduce the dissipated energy per transmitted bit with respect to uncoded communication. Different Low Density Parity Check (LDPC) codes are considered to this purpose and post layout results are shown for a low-area low-energy decoder, which offers percentage energy savings with respect to the uncoded solution in the range of 40%–80%, depending on considered environment, distance and bit error rate. PMID:22438724
Video semaphore decoding for free-space optical communication
Last, Matthew; Fisher, Brian; Ezekwe, Chinwuba; Hubert, Sean M.; Patel, Sheetal; Hollar, Seth; Leibowitz, Brian S.; Pister, Kristofer S. J.
2001-04-01
Using teal-time image processing we have demonstrated a low bit-rate free-space optical communication system at a range of more than 20km with an average optical transmission power of less than 2mW. The transmitter is an autonomous one cubic inch microprocessor-controlled sensor node with a laser diode output. The receiver is a standard CCD camera with a 1-inch aperture lens, and both hardware and software implementations of the video semaphore decoding algorithm. With this system sensor data can be reliably transmitted 21 km form San Francisco to Berkeley.
Simulation of the color vision: decoding quantum-electric transduction
Directory of Open Access Journals (Sweden)
Élgion Lúcio da Silva Loreto
2008-08-01
Full Text Available We propose an experimental simulation, using accessible and low cost materials, on the biophysical mechanism of the color vision in accordance with the Young-Helmholtz s Trichromatic Theory, approaching mainly the coding and decoding process of electric signs that arrive to the cerebral cortex. The stimulus that unchains this process is given through transformation of the quantized energy of a light photon that takes place in the photocells of the retina of the human eye. The construction of a simple system of collection and analysis of data, using a multimeter, filters, LDR and LEDs allows us to establish connections between the visual system and the simulation model.
A Novel Modified Algorithm with Reduced Complexity LDPC Code Decoder
Directory of Open Access Journals (Sweden)
Song Yang
2014-10-01
Full Text Available A novel efficient decoding algorithm reduced the sum-product algorithm (SPA Complexity with LPDC code is proposed. Base on the hyperbolic tangent rule, modified the Check node update with two horizontal process, which have similar calculation, Motivated by the finding that sun- min (MS algorithm reduce the complexity reducing the approximation error in the horizontal process, simplify the information weight small part. Compared with the exiting approximations, the proposed method is less computational complexity than SPA algorithm. Simulation results show that the author algorithm can achieve performance very close SPA.
Abediseid, Walid
2012-01-01
complexity of sphere decoding for the quasi- static, lattice space-time (LAST) coded MIMO channel. Specifically, we drive an upper bound of the tail distribution of the decoder's computational complexity. We show that when the computational complexity exceeds
Decoding and finding the minimum distance with Gröbner bases : history and new insights
Bulygin, S.; Pellikaan, G.R.; Woungang, I.; Misra, S.; Misra, S.C.
2010-01-01
In this chapter, we discuss decoding techniques and finding the minimum distance of linear codes with the use of Grobner bases. First, we give a historical overview of decoding cyclic codes via solving systems polynominal equations over finite fields. In particular, we mention papers of Cooper,.
Video coding and decoding devices and methods preserving ppg relevant information
2013-01-01
The present invention relates to a video encoding device (10) for encoding video data and a corresponding video decoding device, wherein during decoding PPG relevant information shall be preserved. For this purpose the video coding device (10) comprises a first encoder (20) for encoding input video
A Fully Parallel VLSI-implementation of the Viterbi Decoding Algorithm
DEFF Research Database (Denmark)
Sparsø, Jens; Jørgensen, Henrik Nordtorp; Paaske, Erik
1989-01-01
In this paper we describe the implementation of a K = 7, R = 1/2 single-chip Viterbi decoder intended to operate at 10-20 Mbit/sec. We propose a general, regular and area efficient floor-plan that is also suitable for implementation of decoders for codes with different generator polynomials...
Multi-Trial Guruswami–Sudan Decoding for Generalised Reed–Solomon Codes
DEFF Research Database (Denmark)
Nielsen, Johan Sebastian Rosenkilde; Zeh, Alexander
2013-01-01
An iterated refinement procedure for the Guruswami–Sudan list decoding algorithm for Generalised Reed–Solomon codes based on Alekhnovich’s module minimisation is proposed. The method is parametrisable and allows variants of the usual list decoding approach. In particular, finding the list...
The Three Stages of Coding and Decoding in Listening Courses of College Japanese Specialty
Yang, Fang
2008-01-01
The main focus of research papers on listening teaching published in recent years is the theoretical meanings of decoding on the training of listening comprehension ability. Although in many research papers the bottom-up approach and top-down approach, information processing mode theory, are applied to illustrate decoding and to emphasize the…
A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting
Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao
2014-01-01
We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813
Iterative channel decoding of FEC-based multiple-description codes.
Chang, Seok-Ho; Cosman, Pamela C; Milstein, Laurence B
2012-03-01
Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.
Gupta, Neha; Parihar, Priyanka; Neema, Vaibhav
2018-04-01
Researchers have proposed many circuit techniques to reduce leakage power dissipation in memory cells. If we want to reduce the overall power in the memory system, we have to work on the input circuitry of memory architecture i.e. row and column decoder. In this research work, low leakage power with a high speed row and column decoder for memory array application is designed and four new techniques are proposed. In this work, the comparison of cluster DECODER, body bias DECODER, source bias DECODER, and source coupling DECODER are designed and analyzed for memory array application. Simulation is performed for the comparative analysis of different DECODER design parameters at 180 nm GPDK technology file using the CADENCE tool. Simulation results show that the proposed source bias DECODER circuit technique decreases the leakage current by 99.92% and static energy by 99.92% at a supply voltage of 1.2 V. The proposed circuit also improves dynamic power dissipation by 5.69%, dynamic PDP/EDP 65.03% and delay 57.25% at 1.2 V supply voltage.
The Contribution of Attentional Control and Working Memory to Reading Comprehension and Decoding
Arrington, C. Nikki; Kulesz, Paulina A.; Francis, David J.; Fletcher, Jack M.; Barnes, Marcia A.
2014-01-01
Little is known about how specific components of working memory, namely, attentional processes including response inhibition, sustained attention, and cognitive inhibition, are related to reading decoding and comprehension. The current study evaluated the relations of reading comprehension, decoding, working memory, and attentional control in…
Fast N-Gram Language Model Look-Ahead for Decoders With Static Pronunciation Prefix Trees
Huijbregts, M.A.H.; Ordelman, Roeland J.F.; de Jong, Franciska M.G.
2008-01-01
Decoders that make use of token-passing restrict their search space by various types of token pruning. With use of the Language Model Look-Ahead (LMLA) technique it is possible to increase the number of tokens that can be pruned without loss of decoding precision. Unfortunately, for token passing
Scaffolding Students’ Independent Decoding of Unfamiliar Text with a Prototype of an eBook-Feature
DEFF Research Database (Denmark)
Gissel, Stig Toke
2015-01-01
the relevant spelling patterns and in generalizing, in order to strengthen their decoding skills. The prototype was evaluated with Danish students in the second grade to see how and under what circumstances students can use the feature in ways that strengthen their decoding skills and support them in reading...
Hamilton, Stephen; Freed, Erin; Long, Debra L.
2016-01-01
The aim of this study was to examine predictions derived from a proposal about the relation between word-decoding skill and working memory capacity, called verbal efficiency theory. The theory states that poor word representations and slow decoding processes consume resources in working memory that would otherwise be used to execute high-level…
Horikawa, Tomoyasu; Kamitani, Yukiyasu
2017-01-01
Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.
Decoding error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.; Veldhuis, R.; Cronie, H.; Hoeksema, H.
2007-01-01
The decoding of arbitrary linear block codes is accomplished by solving a system of quadratic equations by means of Buchberger’s algorithm for finding a Gröbner basis. This generalizes the algorithm of Berlekamp-Massey for decoding Reed Solomon, Goppa and cyclic codes up to half the true minimum
Bounded distance decoding of linear error-correcting codes with Gröbner bases
Bulygin, S.; Pellikaan, G.R.
2009-01-01
The problem of bounded distance decoding of arbitrary linear codes using Gröbner bases is addressed. A new method is proposed, which is based on reducing an initial decoding problem to solving a certain system of polynomial equations over a finite field. The peculiarity of this system is that, when
A lossy graph model for delay reduction in generalized instantly decodable network coding
Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2014-01-01
, arising from lossy feedback events, when the expected decoding delay of XORing them among themselves or with other certain packets is lower than that expected when sending these packets separately. We compare the decoding delay performance of LG-IDNC and G
Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes
Directory of Open Access Journals (Sweden)
Christine Guillemot
2007-08-01
Full Text Available This paper first introduces a new set of aggregated state models for soft-input decoding of quasi arithmetic (QA codes with a termination constraint. The decoding complexity with these models is linear with the sequence length. The aggregation parameter controls the tradeoff between decoding performance and complexity. It is shown that close-to-optimal decoding performance can be obtained with low values of the aggregation parameter, that is, with a complexity which is significantly reduced with respect to optimal QA bit/symbol models. The choice of the aggregation parameter depends on the synchronization recovery properties of the QA codes. This paper thus describes a method to estimate the probability mass function (PMF of the gain/loss of symbols following a single bit error (i.e., of the difference between the number of encoded and decoded symbols. The entropy of the gain/loss turns out to be the average amount of information conveyed by a length constraint on both the optimal and aggregated state models. This quantity allows us to choose the value of the aggregation parameter that will lead to close-to-optimal decoding performance. It is shown that the optimum position for the length constraint is not the last time instant of the decoding process. This observation leads to the introduction of a new technique for robust decoding of QA codes with redundancy which turns out to outperform techniques based on the concept of forbidden symbol.
Using convolutional decoding to improve time delay and phase estimation in digital communications
Ormesher, Richard C [Albuquerque, NM; Mason, John J [Albuquerque, NM
2010-01-26
The time delay and/or phase of a communication signal received by a digital communication receiver can be estimated based on a convolutional decoding operation that the communication receiver performs on the received communication signal. If the original transmitted communication signal has been spread according to a spreading operation, a corresponding despreading operation can be integrated into the convolutional decoding operation.
Padeliadu, Susana; Antoniou, Faye
2014-01-01
Experts widely consider decoding and fluency as the basis of reading comprehension, while at the same time consistently documenting problems in these areas as major characteristics of students with learning disabilities. However, scholars have developed most of the relevant research within phonologically deep languages, wherein decoding problems…
Tingerthal, John Steven
2013-01-01
Using case study methodology and autoethnographic methods, this study examines a process of curricular development known as "Decoding the Disciplines" (Decoding) by documenting the experience of its application in a construction engineering mechanics course. Motivated by the call to integrate what is known about teaching and learning…
An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata
Seyedi, Saeid; Navimipour, Nima Jafari
2018-03-01
Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.
Row Reduction Applied to Decoding of Rank Metric and Subspace Codes
DEFF Research Database (Denmark)
Puchinger, Sven; Nielsen, Johan Sebastian Rosenkilde; Li, Wenhui
2017-01-01
We show that decoding of ℓ-Interleaved Gabidulin codes, as well as list-ℓ decoding of Mahdavifar–Vardy (MV) codes can be performed by row reducing skew polynomial matrices. Inspired by row reduction of F[x] matrices, we develop a general and flexible approach of transforming matrices over skew...... polynomial rings into a certain reduced form. We apply this to solve generalised shift register problems over skew polynomial rings which occur in decoding ℓ-Interleaved Gabidulin codes. We obtain an algorithm with complexity O(ℓμ2) where μ measures the size of the input problem and is proportional...... to the code length n in the case of decoding. Further, we show how to perform the interpolation step of list-ℓ-decoding MV codes in complexity O(ℓn2), where n is the number of interpolation constraints....
Locating and decoding barcodes in fuzzy images captured by smart phones
Deng, Wupeng; Hu, Jiwei; Liu, Quan; Lou, Ping
2017-07-01
With the development of barcodes for commercial use, people's requirements for detecting barcodes by smart phone become increasingly pressing. The low quality of barcode image captured by mobile phone always affects the decoding and recognition rates. This paper focuses on locating and decoding EAN-13 barcodes in fuzzy images. We present a more accurate locating algorithm based on segment length and high fault-tolerant rate algorithm for decoding barcodes. Unlike existing approaches, location algorithm is based on the edge segment length of EAN -13 barcodes, while our decoding algorithm allows the appearance of fuzzy region in barcode image. Experimental results are performed on damaged, contaminated and scratched digital images, and provide a quite promising result for EAN -13 barcode location and decoding.
Efficient Dual Domain Decoding of Linear Block Codes Using Genetic Algorithms
Directory of Open Access Journals (Sweden)
Ahmed Azouaoui
2012-01-01
Full Text Available A computationally efficient algorithm for decoding block codes is developed using a genetic algorithm (GA. The proposed algorithm uses the dual code in contrast to the existing genetic decoders in the literature that use the code itself. Hence, this new approach reduces the complexity of decoding the codes of high rates. We simulated our algorithm in various transmission channels. The performance of this algorithm is investigated and compared with competitor decoding algorithms including Maini and Shakeel ones. The results show that the proposed algorithm gives large gains over the Chase-2 decoding algorithm and reach the performance of the OSD-3 for some quadratic residue (QR codes. Further, we define a new crossover operator that exploits the domain specific information and compare it with uniform and two point crossover. The complexity of this algorithm is also discussed and compared to other algorithms.
Iterative Decoding for an Optical CDMA based Laser communication System
International Nuclear Information System (INIS)
Kim, Jin Young; Kim, Eun Cheol; Cha, Jae Sang
2008-01-01
An optical CDMA(code division multiple access)based Laser communication system has attracted much attention since it requires minimal optical Laser signal processing and it is virtually delay free, while from the theoretical point of view, its performance depends on the auto and cross correlation properties of employed sequences. Various kinds of channel coding schemes for optical CDMA based Laser communication systems have been proposed and analyzed to compensate nonideal channel and receiver conditions in impaired photon channels. In this paper, we propose and analyze an iterative decoding of optical CDMA based Laser communication signals for both shot noise limited and thermal noise limited systems. It is assumed that optical channel is an intensity modulated (IM)channel and direct detection scheme is employed to detect the received optical signal. The performance is evaluated in terms of bit error probability and throughput. It is demonstrated that the BER and throughput performance is substantially improved with interleaver length for a fixed code rate and with alphabet size of PPM (pulse position modulation). Also, the BER and throughput performance is significantly enhanced with the number of iterations for decoding process. The results in this paper can be applied to the optical CDMA based Laser communication network with multiple access applications
Neural signatures of attention: insights from decoding population activity patterns.
Sapountzis, Panagiotis; Gregoriou, Georgia G
2018-01-01
Understanding brain function and the computations that individual neurons and neuronal ensembles carry out during cognitive functions is one of the biggest challenges in neuroscientific research. To this end, invasive electrophysiological studies have provided important insights by recording the activity of single neurons in behaving animals. To average out noise, responses are typically averaged across repetitions and across neurons that are usually recorded on different days. However, the brain makes decisions on short time scales based on limited exposure to sensory stimulation by interpreting responses of populations of neurons on a moment to moment basis. Recent studies have employed machine-learning algorithms in attention and other cognitive tasks to decode the information content of distributed activity patterns across neuronal ensembles on a single trial basis. Here, we review results from studies that have used pattern-classification decoding approaches to explore the population representation of cognitive functions. These studies have offered significant insights into population coding mechanisms. Moreover, we discuss how such advances can aid the development of cognitive brain-computer interfaces.
Iterative Decoding for an Optical CDMA based Laser communication System
Energy Technology Data Exchange (ETDEWEB)
Kim, Jin Young; Kim, Eun Cheol [Kwangwoon Univ., Seoul (Korea, Republic of); Cha, Jae Sang [Seoul National Univ. of Technology, Seoul (Korea, Republic of)
2008-11-15
An optical CDMA(code division multiple access)based Laser communication system has attracted much attention since it requires minimal optical Laser signal processing and it is virtually delay free, while from the theoretical point of view, its performance depends on the auto and cross correlation properties of employed sequences. Various kinds of channel coding schemes for optical CDMA based Laser communication systems have been proposed and analyzed to compensate nonideal channel and receiver conditions in impaired photon channels. In this paper, we propose and analyze an iterative decoding of optical CDMA based Laser communication signals for both shot noise limited and thermal noise limited systems. It is assumed that optical channel is an intensity modulated (IM)channel and direct detection scheme is employed to detect the received optical signal. The performance is evaluated in terms of bit error probability and throughput. It is demonstrated that the BER and throughput performance is substantially improved with interleaver length for a fixed code rate and with alphabet size of PPM (pulse position modulation). Also, the BER and throughput performance is significantly enhanced with the number of iterations for decoding process. The results in this paper can be applied to the optical CDMA based Laser communication network with multiple access applications.
Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy
International Nuclear Information System (INIS)
Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong
2015-01-01
The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique
Discrete decoding based ultrafast multidimensional nuclear magnetic resonance spectroscopy
Wei, Zhiliang; Lin, Liangjie; Ye, Qimiao; Li, Jing; Cai, Shuhui; Chen, Zhong
2015-07-01
The three-dimensional (3D) nuclear magnetic resonance (NMR) spectroscopy constitutes an important and powerful tool in analyzing chemical and biological systems. However, the abundant 3D information arrives at the expense of long acquisition times lasting hours or even days. Therefore, there has been a continuous interest in developing techniques to accelerate recordings of 3D NMR spectra, among which the ultrafast spatiotemporal encoding technique supplies impressive acquisition speed by compressing a multidimensional spectrum in a single scan. However, it tends to suffer from tradeoffs among spectral widths in different dimensions, which deteriorates in cases of NMR spectroscopy with more dimensions. In this study, the discrete decoding is proposed to liberate the ultrafast technique from tradeoffs among spectral widths in different dimensions by focusing decoding on signal-bearing sites. For verifying its feasibility and effectiveness, we utilized the method to generate two different types of 3D spectra. The proposed method is also applicable to cases with more than three dimensions, which, based on the experimental results, may widen applications of the ultrafast technique.
Artificial spatiotemporal touch inputs reveal complementary decoding in neocortical neurons.
Oddo, Calogero M; Mazzoni, Alberto; Spanne, Anton; Enander, Jonas M D; Mogensen, Hannes; Bengtsson, Fredrik; Camboni, Domenico; Micera, Silvestro; Jörntell, Henrik
2017-04-04
Investigations of the mechanisms of touch perception and decoding has been hampered by difficulties in achieving invariant patterns of skin sensor activation. To obtain reproducible spatiotemporal patterns of activation of sensory afferents, we used an artificial fingertip equipped with an array of neuromorphic sensors. The artificial fingertip was used to transduce real-world haptic stimuli into spatiotemporal patterns of spikes. These spike patterns were delivered to the skin afferents of the second digit of rats via an array of stimulation electrodes. Combined with low-noise intra- and extracellular recordings from neocortical neurons in vivo, this approach provided a previously inaccessible high resolution analysis of the representation of tactile information in the neocortical neuronal circuitry. The results indicate high information content in individual neurons and reveal multiple novel neuronal tactile coding features such as heterogeneous and complementary spatiotemporal input selectivity also between neighboring neurons. Such neuronal heterogeneity and complementariness can potentially support a very high decoding capacity in a limited population of neurons. Our results also indicate a potential neuroprosthetic approach to communicate with the brain at a very high resolution and provide a potential novel solution for evaluating the degree or state of neurological disease in animal models.
Decoding Problem Gamblers' Signals: A Decision Model for Casino Enterprises.
Ifrim, Sandra
2015-12-01
The aim of the present study is to offer a validated decision model for casino enterprises. The model enables those users to perform early detection of problem gamblers and fulfill their ethical duty of social cost minimization. To this end, the interpretation of casino customers' nonverbal communication is understood as a signal-processing problem. Indicators of problem gambling recommended by Delfabbro et al. (Identifying problem gamblers in gambling venues: final report, 2007) are combined with Viterbi algorithm into an interdisciplinary model that helps decoding signals emitted by casino customers. Model output consists of a historical path of mental states and cumulated social costs associated with a particular client. Groups of problem and non-problem gamblers were simulated to investigate the model's diagnostic capability and its cost minimization ability. Each group consisted of 26 subjects and was subsequently enlarged to 100 subjects. In approximately 95% of the cases, mental states were correctly decoded for problem gamblers. Statistical analysis using planned contrasts revealed that the model is relatively robust to the suppression of signals performed by casino clientele facing gambling problems as well as to misjudgments made by staff regarding the clients' mental states. Only if the last mentioned source of error occurs in a very pronounced manner, i.e. judgment is extremely faulty, cumulated social costs might be distorted.
Hardwarearchitektur für einen universellen LDPC Decoder
Directory of Open Access Journals (Sweden)
C. Beuschel
2009-05-01
Full Text Available Im vorliegenden Beitrag wird eine universelle Decoderarchitektur für einen Low-Density Parity-Check (LDPC Code Decoder vorgestellt. Anders als bei den in der Literatur häufig beschriebenen Architekturen für strukturierte Codes ist die hier vorgestellte Architektur frei programmierbar, so dass jeder beliebige LDPC Code durch eine Änderung der Initialisierung des Speichers für die Prüfmatrix mit derselben Hardware decodiert werden kann. Die größte Herausforderung beim Entwurf von teilparallelen LDPC Decoder Architekturen liegt im konfliktfreien Datenaustausch zwischen mehreren parallelen Speichern und Berechnungseinheiten, wozu ein Mapping und Scheduling Algorithmus benötigt wird. Der hier vorgestellte Algorithmus stützt sich auf Graphentheorie und findet für jeden beliebigen LDPC Code eine für die Architektur optimale Lösung. Damit sind keine Wartezyklen notwendig und die Parallelität der Architektur wird zu jedem Zeitpunkt voll ausgenutzt.
Frame Decoder for Consultative Committee for Space Data Systems (CCSDS)
Reyes, Miguel A. De Jesus
2014-01-01
GNU Radio is a free and open source development toolkit that provides signal processing to implement software radios. It can be used with low-cost external RF hardware to create software defined radios, or without hardware in a simulation-like environment. GNU Radio applications are primarily written in Python and C++. The Universal Software Radio Peripheral (USRP) is a computer-hosted software radio designed by Ettus Research. The USRP connects to a host computer via high-speed Gigabit Ethernet. Using the open source Universal Hardware Driver (UHD), we can run GNU Radio applications using the USRP. An SDR is a "radio in which some or all physical layer functions are software defined"(IEEE Definition). A radio is any kind of device that wirelessly transmits or receives radio frequency (RF) signals in the radio frequency. An SDR is a radio communication system where components that have been typically implemented in hardware are implemented in software. GNU Radio has a generic packet decoder block that is not optimized for CCSDS frames. Using this generic packet decoder will add bytes to the CCSDS frames and will not permit for bit error correction using Reed-Solomon. The CCSDS frames consist of 256 bytes, including a 32-bit sync marker (0x1ACFFC1D). This frames are generated by the Space Data Processor and GNU Radio will perform the modulation and framing operations, including frame synchronization.
Mapping of MPEG-4 decoding on a flexible architecture platform
van der Tol, Erik B.; Jaspers, Egbert G.
2001-12-01
In the field of consumer electronics, the advent of new features such as Internet, games, video conferencing, and mobile communication has triggered the convergence of television and computers technologies. This requires a generic media-processing platform that enables simultaneous execution of very diverse tasks such as high-throughput stream-oriented data processing and highly data-dependent irregular processing with complex control flows. As a representative application, this paper presents the mapping of a Main Visual profile MPEG-4 for High-Definition (HD) video onto a flexible architecture platform. A stepwise approach is taken, going from the decoder application toward an implementation proposal. First, the application is decomposed into separate tasks with self-contained functionality, clear interfaces, and distinct characteristics. Next, a hardware-software partitioning is derived by analyzing the characteristics of each task such as the amount of inherent parallelism, the throughput requirements, the complexity of control processing, and the reuse potential over different applications and different systems. Finally, a feasible implementation is proposed that includes amongst others a very-long-instruction-word (VLIW) media processor, one or more RISC processors, and some dedicated processors. The mapping study of the MPEG-4 decoder proves the flexibility and extensibility of the media-processing platform. This platform enables an effective HW/SW co-design yielding a high performance density.
A method for decoding the neurophysiological spike-response transform.
Stern, Estee; García-Crescioni, Keyla; Miller, Mark W; Peskin, Charles S; Brezina, Vladimir
2009-11-15
Many physiological responses elicited by neuronal spikes-intracellular calcium transients, synaptic potentials, muscle contractions-are built up of discrete, elementary responses to each spike. However, the spikes occur in trains of arbitrary temporal complexity, and each elementary response not only sums with previous ones, but can itself be modified by the previous history of the activity. A basic goal in system identification is to characterize the spike-response transform in terms of a small number of functions-the elementary response kernel and additional kernels or functions that describe the dependence on previous history-that will predict the response to any arbitrary spike train. Here we do this by developing further and generalizing the "synaptic decoding" approach of Sen et al. (1996). Given the spike times in a train and the observed overall response, we use least-squares minimization to construct the best estimated response and at the same time best estimates of the elementary response kernel and the other functions that characterize the spike-response transform. We avoid the need for any specific initial assumptions about these functions by using techniques of mathematical analysis and linear algebra that allow us to solve simultaneously for all of the numerical function values treated as independent parameters. The functions are such that they may be interpreted mechanistically. We examine the performance of the method as applied to synthetic data. We then use the method to decode real synaptic and muscle contraction transforms.
Decoding rule search domain in the left inferior frontal gyrus
Babcock, Laura; Vallesi, Antonino
2018-01-01
Traditionally, the left hemisphere has been thought to extract mainly verbal patterns of information, but recent evidence has shown that the left Inferior Frontal Gyrus (IFG) is active during inductive reasoning in both the verbal and spatial domains. We aimed to understand whether the left IFG supports inductive reasoning in a domain-specific or domain-general fashion. To do this we used Multi-Voxel Pattern Analysis to decode the representation of domain during a rule search task. Thirteen participants were asked to extract the rule underlying streams of letters presented in different spatial locations. Each rule was either verbal (letters forming words) or spatial (positions forming geometric figures). Our results show that domain was decodable in the left prefrontal cortex, suggesting that this region represents domain-specific information, rather than processes common to the two domains. A replication study with the same participants tested two years later confirmed these findings, though the individual representations changed, providing evidence for the flexible nature of representations. This study extends our knowledge on the neural basis of goal-directed behaviors and on how information relevant for rule extraction is flexibly mapped in the prefrontal cortex. PMID:29547623
Successful decoding of famous faces in the fusiform face area.
Directory of Open Access Journals (Sweden)
Vadim Axelrod
Full Text Available What are the neural mechanisms of face recognition? It is believed that the network of face-selective areas, which spans the occipital, temporal, and frontal cortices, is important in face recognition. A number of previous studies indeed reported that face identity could be discriminated based on patterns of multivoxel activity in the fusiform face area and the anterior temporal lobe. However, given the difficulty in localizing the face-selective area in the anterior temporal lobe, its role in face recognition is still unknown. Furthermore, previous studies limited their analysis to occipito-temporal regions without testing identity decoding in more anterior face-selective regions, such as the amygdala and prefrontal cortex. In the current high-resolution functional Magnetic Resonance Imaging study, we systematically examined the decoding of the identity of famous faces in the temporo-frontal network of face-selective and adjacent non-face-selective regions. A special focus has been put on the face-area in the anterior temporal lobe, which was reliably localized using an optimized scanning protocol. We found that face-identity could be discriminated above chance level only in the fusiform face area. Our results corroborate the role of the fusiform face area in face recognition. Future studies are needed to further explore the role of the more recently discovered anterior face-selective areas in face recognition.
Joint Carrier-Phase Synchronization and LDPC Decoding
Simon, Marvin; Valles, Esteban
2009-01-01
A method has been proposed to increase the degree of synchronization of a radio receiver with the phase of a suppressed carrier signal modulated with a binary- phase-shift-keying (BPSK) or quaternary- phase-shift-keying (QPSK) signal representing a low-density parity-check (LDPC) code. This method is an extended version of the method described in Using LDPC Code Constraints to Aid Recovery of Symbol Timing (NPO-43112), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 54. Both methods and the receiver architectures in which they would be implemented belong to a class of timing- recovery methods and corresponding receiver architectures characterized as pilotless in that they do not require transmission and reception of pilot signals. The proposed method calls for the use of what is known in the art as soft decision feedback to remove the modulation from a replica of the incoming signal prior to feeding this replica to a phase-locked loop (PLL) or other carrier-tracking stage in the receiver. Soft decision feedback refers to suitably processed versions of intermediate results of iterative computations involved in the LDPC decoding process. Unlike a related prior method in which hard decision feedback (the final sequence of decoded symbols) is used to remove the modulation, the proposed method does not require estimation of the decoder error probability. In a basic digital implementation of the proposed method, the incoming signal (having carrier phase theta theta (sub c) plus noise would first be converted to inphase (I) and quadrature (Q) baseband signals by mixing it with I and Q signals at the carrier frequency [wc/(2 pi)] generated by a local oscillator. The resulting demodulated signals would be processed through one-symbol-period integrate and- dump filters, the outputs of which would be sampled and held, then multiplied by a soft-decision version of the baseband modulated signal. The resulting I and Q products consist of terms proportional to the cosine
Low Complexity List Decoding for Polar Codes with Multiple CRC Codes
Directory of Open Access Journals (Sweden)
Jong-Hwan Kim
2017-04-01
Full Text Available Polar codes are the first family of error correcting codes that provably achieve the capacity of symmetric binary-input discrete memoryless channels with low complexity. Since the development of polar codes, there have been many studies to improve their finite-length performance. As a result, polar codes are now adopted as a channel code for the control channel of 5G new radio of the 3rd generation partnership project. However, the decoder implementation is one of the big practical problems and low complexity decoding has been studied. This paper addresses a low complexity successive cancellation list decoding for polar codes utilizing multiple cyclic redundancy check (CRC codes. While some research uses multiple CRC codes to reduce memory and time complexity, we consider the operational complexity of decoding, and reduce it by optimizing CRC positions in combination with a modified decoding operation. Resultingly, the proposed scheme obtains not only complexity reduction from early stopping of decoding, but also additional reduction from the reduced number of decoding paths.
On the decoding process in ternary error-correcting output codes.
Escalera, Sergio; Pujol, Oriol; Radeva, Petia
2010-01-01
A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successful framework to deal with these type of problems. Recent works in the ECOC framework showed significant performance improvements by means of new problem-dependent designs based on the ternary ECOC framework. The ternary framework contains a larger set of binary problems because of the use of a "do not care" symbol that allows us to ignore some classes by a given classifier. However, there are no proper studies that analyze the effect of the new symbol at the decoding step. In this paper, we present a taxonomy that embeds all binary and ternary ECOC decoding strategies into four groups. We show that the zero symbol introduces two kinds of biases that require redefinition of the decoding design. A new type of decoding measure is proposed, and two novel decoding strategies are defined. We evaluate the state-of-the-art coding and decoding strategies over a set of UCI Machine Learning Repository data sets and into a real traffic sign categorization problem. The experimental results show that, following the new decoding strategies, the performance of the ECOC design is significantly improved.
Cellular automaton decoders of topological quantum memories in the fault tolerant setting
International Nuclear Information System (INIS)
Herold, Michael; Eisert, Jens; Kastoryano, Michael J; Campbell, Earl T
2017-01-01
Active error decoding and correction of topological quantum codes—in particular the toric code—remains one of the most viable routes to large scale quantum information processing. In contrast, passive error correction relies on the natural physical dynamics of a system to protect encoded quantum information. However, the search is ongoing for a completely satisfactory passive scheme applicable to locally interacting two-dimensional systems. Here, we investigate dynamical decoders that provide passive error correction by embedding the decoding process into local dynamics. We propose a specific discrete time cellular-automaton decoder in the fault tolerant setting and provide numerical evidence showing that the logical qubit has a survival time extended by several orders of magnitude over that of a bare unencoded qubit. We stress that (asynchronous) dynamical decoding gives rise to a Markovian dissipative process. We hence equate cellular-automaton decoding to a fully dissipative topological quantum memory, which removes errors continuously. In this sense, uncontrolled and unwanted local noise can be corrected for by a controlled local dissipative process. We analyze the required resources, commenting on additional polylogarithmic factors beyond those incurred by an ideal constant resource dynamical decoder. (paper)
Fast and Flexible Successive-Cancellation List Decoders for Polar Codes
Hashemi, Seyyed Ali; Condo, Carlo; Gross, Warren J.
2017-11-01
Polar codes have gained significant amount of attention during the past few years and have been selected as a coding scheme for the next generation of mobile broadband standard. Among decoding schemes, successive-cancellation list (SCL) decoding provides a reasonable trade-off between the error-correction performance and hardware implementation complexity when used to decode polar codes, at the cost of limited throughput. The simplified SCL (SSCL) and its extension SSCL-SPC increase the speed of decoding by removing redundant calculations when encountering particular information and frozen bit patterns (rate one and single parity check codes), while keeping the error-correction performance unaltered. In this paper, we improve SSCL and SSCL-SPC by proving that the list size imposes a specific number of bit estimations required to decode rate one and single parity check codes. Thus, the number of estimations can be limited while guaranteeing exactly the same error-correction performance as if all bits of the code were estimated. We call the new decoding algorithms Fast-SSCL and Fast-SSCL-SPC. Moreover, we show that the number of bit estimations in a practical application can be tuned to achieve desirable speed, while keeping the error-correction performance almost unchanged. Hardware architectures implementing both algorithms are then described and implemented: it is shown that our design can achieve 1.86 Gb/s throughput, higher than the best state-of-the-art decoders.
ESVD: An Integrated Energy Scalable Framework for Low-Power Video Decoding Systems
Directory of Open Access Journals (Sweden)
Wen Ji
2010-01-01
Full Text Available Video applications using mobile wireless devices are a challenging task due to the limited capacity of batteries. The higher complex functionality of video decoding needs high resource requirements. Thus, power efficient control has become more critical design with devices integrating complex video processing techniques. Previous works on power efficient control in video decoding systems often aim at the low complexity design and not explicitly consider the scalable impact of subfunctions in decoding process, and seldom consider the relationship with the features of compressed video date. This paper is dedicated to developing an energy-scalable video decoding (ESVD strategy for energy-limited mobile terminals. First, ESVE can dynamically adapt the variable energy resources due to the device aware technique. Second, ESVD combines the decoder control with decoded data, through classifying the data into different partition profiles according to its characteristics. Third, it introduces utility theoretical analysis during the resource allocation process, so as to maximize the resource utilization. Finally, it adapts the energy resource as different energy budget and generates the scalable video decoding output under energy-limited systems. Experimental results demonstrate the efficiency of the proposed approach.
Prior Knowledge Improves Decoding of Finger Flexion from Electrocorticographic (ECoG Signals
Directory of Open Access Journals (Sweden)
Zuoguan eWang
2011-11-01
Full Text Available Brain-computer interfaces (BCIs use brain signals to convey a user's intent. Some BCI approaches begin by decoding kinematic parameters of movements from brain signals, and then proceed to using these signals, in absence of movements, to allow a user to control an output. Recent results have shown that electrocorticographic (ECoG recordings from the surface of the brain in humans can give information about kinematic parameters (eg{} hand velocity or finger flexion. The decoding approaches in these studies usually employed classical classification/regression algorithms that derive a linear mapping between brain signals and outputs. However, they typically only incorporate little prior information about the target movement parameter. In this paper, we incorporate prior knowledge using a Bayesian decoding method, and use it to decode finger flexion from ECoG signals. Specifically, we exploit the anatomic constraints and dynamic constraints that govern finger flexion and incorporate these constraints in the construction, structure, and the probabilistic functions of the prior model of a switched non-parametric dynamic system (SNDS. Given a measurement model resulting from a traditional linear regression method, we decoded finger flexion using posterior estimation that combined the prior and measurement models. Our results show that the application of the Bayesian decoding model, which incorporates prior knowledge, improves decoding performance compared to the application of a linear regression model, which does not incorporate prior knowledge. Thus, the results presented in this paper may ultimately lead to neurally controlled hand prostheses with full fine-grained finger articulation.
Clusterless Decoding of Position From Multiunit Activity Using A Marked Point Process Filter
Deng, Xinyi; Liu, Daniel F.; Kay, Kenneth; Frank, Loren M.; Eden, Uri T.
2016-01-01
Point process filters have been applied successfully to decode neural signals and track neural dynamics. Traditionally, these methods assume that multiunit spiking activity has already been correctly spike-sorted. As a result, these methods are not appropriate for situations where sorting cannot be performed with high precision such as real-time decoding for brain-computer interfaces. As the unsupervised spike-sorting problem remains unsolved, we took an alternative approach that takes advantage of recent insights about clusterless decoding. Here we present a new point process decoding algorithm that does not require multiunit signals to be sorted into individual units. We use the theory of marked point processes to construct a function that characterizes the relationship between a covariate of interest (in this case, the location of a rat on a track) and features of the spike waveforms. In our example, we use tetrode recordings, and the marks represent a four-dimensional vector of the maximum amplitudes of the spike waveform on each of the four electrodes. In general, the marks may represent any features of the spike waveform. We then use Bayes’ rule to estimate spatial location from hippocampal neural activity. We validate our approach with a simulation study and with experimental data recorded in the hippocampus of a rat moving through a linear environment. Our decoding algorithm accurately reconstructs the rat’s position from unsorted multiunit spiking activity. We then compare the quality of our decoding algorithm to that of a traditional spike-sorting and decoding algorithm. Our analyses show that the proposed decoding algorithm performs equivalently or better than algorithms based on sorted single-unit activity. These results provide a path toward accurate real-time decoding of spiking patterns that could be used to carry out content-specific manipulations of population activity in hippocampus or elsewhere in the brain. PMID:25973549
Decoding the Nature of Emotion in the Brain.
Kragel, Philip A; LaBar, Kevin S
2016-06-01
A central, unresolved problem in affective neuroscience is understanding how emotions are represented in nervous system activity. After prior localization approaches largely failed, researchers began applying multivariate statistical tools to reconceptualize how emotion constructs might be embedded in large-scale brain networks. Findings from pattern analyses of neuroimaging data show that affective dimensions and emotion categories are uniquely represented in the activity of distributed neural systems that span cortical and subcortical regions. Results from multiple-category decoding studies are incompatible with theories postulating that specific emotions emerge from the neural coding of valence and arousal. This 'new look' into emotion representation promises to improve and reformulate neurobiological models of affect. Copyright © 2016 Elsevier Ltd. All rights reserved.
Probabilistic Amplitude Shaping With Hard Decision Decoding and Staircase Codes
Sheikh, Alireza; Amat, Alexandre Graell i.; Liva, Gianluigi; Steiner, Fabian
2018-05-01
We consider probabilistic amplitude shaping (PAS) as a means of increasing the spectral efficiency of fiber-optic communication systems. In contrast to previous works in the literature, we consider probabilistic shaping with hard decision decoding (HDD). In particular, we apply the PAS recently introduced by B\\"ocherer \\emph{et al.} to a coded modulation (CM) scheme with bit-wise HDD that uses a staircase code as the forward error correction code. We show that the CM scheme with PAS and staircase codes yields significant gains in spectral efficiency with respect to the baseline scheme using a staircase code and a standard constellation with uniformly distributed signal points. Using a single staircase code, the proposed scheme achieves performance within $0.57$--$1.44$ dB of the corresponding achievable information rate for a wide range of spectral efficiencies.
Coding and decoding for code division multiple user communication systems
Healy, T. J.
1985-01-01
A new algorithm is introduced which decodes code division multiple user communication signals. The algorithm makes use of the distinctive form or pattern of each signal to separate it from the composite signal created by the multiple users. Although the algorithm is presented in terms of frequency-hopped signals, the actual transmitter modulator can use any of the existing digital modulation techniques. The algorithm is applicable to error-free codes or to codes where controlled interference is permitted. It can be used when block synchronization is assumed, and in some cases when it is not. The paper also discusses briefly some of the codes which can be used in connection with the algorithm, and relates the algorithm to past studies which use other approaches to the same problem.
Efficiency turns the table on neural encoding, decoding and noise.
Deneve, Sophie; Chalk, Matthew
2016-04-01
Sensory neurons are usually described with an encoding model, for example, a function that predicts their response from the sensory stimulus using a receptive field (RF) or a tuning curve. However, central to theories of sensory processing is the notion of 'efficient coding'. We argue here that efficient coding implies a completely different neural coding strategy. Instead of a fixed encoding model, neural populations would be described by a fixed decoding model (i.e. a model reconstructing the stimulus from the neural responses). Because the population solves a global optimization problem, individual neurons are variable, but not noisy, and have no truly invariant tuning curve or receptive field. We review recent experimental evidence and implications for neural noise correlations, robustness and adaptation. Copyright © 2016. Published by Elsevier Ltd.
Brief report: decoding representations: how children with autism understand drawings.
Allen, Melissa L
2009-03-01
Young typically developing children can reason about abstract depictions if they know the intention of the artist. Children with autism spectrum disorder (ASD), who are notably impaired in social, 'intention monitoring' domains, may have great difficulty in decoding vague representations. In Experiment 1, children with ASD are unable to use another person's eye gaze as a cue for figuring out what an abstract picture represents. In contrast, when the participants themselves are the artists (Experiment 2), children with ASD are equally proficient as controls at identifying their own perceptually identical pictures (e.g. lollipop and balloon) after a delay, based upon what they intended them to be. Results are discussed in terms of intention and understanding of visual representation in autism.
Decoding Computer Games: Studying “Special Operation 85”
Directory of Open Access Journals (Sweden)
Bahareh Jalalzadeh
2009-11-01
Full Text Available As other media, computer games convey messages which have tow features: explicit and implicit. Semiologically studying computer games and comparing them with narrative structures, the present study attempts to discover the messages they convey. Therefore we have studied and decoded “Special operation 85” as a semiological text. Results show that the game’s features, as naming, interests and motivations of the engaged people, and the events narrated, all lead the producers to their goals of introducing and publicizing Iranian-Islamic cultural values. Although this feature makes “Special Opreation 85” a unique game, it fails in its attempt to produce a mythical personage in Iranian-Islamic cultural context.
Exact performance analysis of decode-and-forward opportunistic relaying
Tourki, Kamel
2010-06-01
In this paper, we investigate a dual-hop decode-and-forward opportunistic relaying scheme where the source may or may not be able to communicate directly with the destination. In our study, we consider a regenerative relaying scheme in which the decision to cooperate takes into account the effect of the possible erroneously detected and transmitted data at the best relay. We derive an exact closed-form expression for the end-to-end bit-error rate (BER) of binary phase-shift keying (BPSK) modulation based on the exact statistics of each hop. Unlike existing works where the analysis focused on high signal-to-noise ratio (SNR) regime, such results are important to enable the designers to take decisions regarding practical systems that operate at low SNR regime. We show that performance simulation results coincide with our analytical results.
Decoding a combined amplitude modulated and frequency modulated signal
DEFF Research Database (Denmark)
2015-01-01
The present disclosure relates to a method for decoding a combined AM/FM encoded signal, comprising the steps of: combining said encoded optical signal with light from a local oscillator configured with a local oscillator frequency; converting the combined local oscillator and encoded optical...... signal into one or more electrical signals by means of at least one opto-electrical converter having a predefined frequency bandwidth, thereby providing an amplified and encoded electrical signal having one or more encoded signal current(s), where one type of states have a higher oscillation frequency...... than other type of states; rectifying the encoded signal current(s), thereby obtaining an encoded power spectrum, wherein said power spectrum has different states, such as "0"-states and "1"-states, with different power levels such that they can be discriminated, said local oscillator frequency...
Selection combining for noncoherent decode-and-forward relay networks
Directory of Open Access Journals (Sweden)
Nguyen Ha
2011-01-01
Full Text Available Abstract This paper studies a new decode-and-forward relaying scheme for a cooperative wireless network composed of one source, K relays, and one destination and with binary frequency-shift keying modulation. A single threshold is employed to select retransmitting relays as follows: a relay retransmits to the destination if its decision variable is larger than the threshold; otherwise, it remains silent. The destination then performs selection combining for the detection of transmitted information. The average end-to-end bit-error-rate (BER is analytically determined in a closed-form expression. Based on the derived BER, the problem of choosing an optimal threshold or jointly optimal threshold and power allocation to minimize the end-to-end BER is also investigated. Both analytical and simulation results reveal that the obtained optimal threshold scheme or jointly optimal threshold and power-allocation scheme can significantly improve the BER performance compared to a previously proposed scheme.
Motor-commands decoding using peripheral nerve signals: a review
Hong, Keum-Shik; Aziz, Nida; Ghafoor, Usman
2018-06-01
During the last few decades, substantial scientific and technological efforts have been focused on the development of neuroprostheses. The major emphasis has been on techniques for connecting the human nervous system with a robotic prosthesis via natural-feeling interfaces. The peripheral nerves provide access to highly processed and segregated neural command signals from the brain that can in principle be used to determine user intent and control muscles. If these signals could be used, they might allow near-natural and intuitive control of prosthetic limbs with multiple degrees of freedom. This review summarizes the history of neuroprosthetic interfaces and their ability to record from and stimulate peripheral nerves. We also discuss the types of interfaces available and their applications, the kinds of peripheral nerve signals that are used, and the algorithms used to decode them. Finally, we explore the prospects for future development in this area.
Outage analysis of opportunistic decode-and-forward relaying
Tourki, Kamel
2010-09-01
In this paper, we investigate a dual-hop opportunistic decode-and-forward relaying scheme where the source may or not be able to communicate directly with the destination. We first derive statistics based on exact probability density function (PDF) of each hop. Then, the PDFs are used to determine closed-form outage probability expression for a transmission rate R. Furthermore, we evaluate the asymptotic outage performance and the diversity order is deduced. Unlike existing works where the analysis focused on high signal-to-noise ratio (SNR) regime, such results are important to enable the designers to take decisions regarding practical systems that operate at low SNR regime. We show that performance simulation results coincide with our analytical results under practical assumption of unbalanced hops. © 2010 IEEE.
Remote Control and Testing of the Interactive TV-Decoder
Directory of Open Access Journals (Sweden)
K. Vlcek
1995-12-01
Full Text Available The article deals with assembling and application of a complex sequential circuit VHDL (VHSIC (Very High-Speed Integrated Circuit Hardware Description Language model. The circuit model is a core of a cryptographic device for the signal encoding and decoding of discreet transmissions by TV-cable net. The cryptographic algorithm is changable according to the user's wishes. The principles of creation and example implementations are presented in the article. The behavioural model is used to minimize mistakes in the ASICs (Application Specific Integrated Circuits. The circuit implementation uses the FPGA (Field Programmable Gate Array technology. The diagnostics of the circuit is based on remote testing by the IEEE Std 1149.1-1990. The VHDL model of diagnostic subsystem is created as an orthogonal model in relation to the cryptographic circuit VHDL model.
Generalized instantly decodable network coding for relay-assisted networks
Elmahdy, Adel M.
2013-09-01
In this paper, we investigate the problem of minimizing the frame completion delay for Instantly Decodable Network Coding (IDNC) in relay-assisted wireless multicast networks. We first propose a packet recovery algorithm in the single relay topology which employs generalized IDNC instead of strict IDNC previously proposed in the literature for the same relay-assisted topology. This use of generalized IDNC is supported by showing that it is a super-set of the strict IDNC scheme, and thus can generate coding combinations that are at least as efficient as strict IDNC in reducing the average completion delay. We then extend our study to the multiple relay topology and propose a joint generalized IDNC and relay selection algorithm. This proposed algorithm benefits from the reception diversity of the multiple relays to further reduce the average completion delay in the network. Simulation results show that our proposed solutions achieve much better performance compared to previous solutions in the literature. © 2013 IEEE.
Using Social Scientific Criteria to Evaluate Cultural Theories: Encoding/Decoding Evaluated
Directory of Open Access Journals (Sweden)
Evan L. Kropp
2015-12-01
Full Text Available This article transcends the issue of conflicting theoretical schools of thought to formulate a method of social scientific style theory evaluation for cultural studies. It is suggested that positivist social scientific models of theory critique can be used to assess cultural models of communication to determine if they should be classified as theories. A set of evaluation criteria is formulated as a guide and applied to Stuart Hall’s Encoding/Decoding to determine if it is a theory. Conclusions find the sharing of criteria between schools of thought is judicious, Encoding/Decoding fits the established criteria, and Encoding/Decoding should be referred to as a theory.
Mutiple LDPC Decoding using Bitplane Correlation for Transform Domain Wyner-Ziv Video Coding
DEFF Research Database (Denmark)
Luong, Huynh Van; Huang, Xin; Forchhammer, Søren
2011-01-01
Distributed video coding (DVC) is an emerging video coding paradigm for systems which fully or partly exploit the source statistics at the decoder to reduce the computational burden at the encoder. This paper considers a Low Density Parity Check (LDPC) based Transform Domain Wyner-Ziv (TDWZ) video...... codec. To improve the LDPC coding performance in the context of TDWZ, this paper proposes a Wyner-Ziv video codec using bitplane correlation through multiple parallel LDPC decoding. The proposed scheme utilizes inter bitplane correlation to enhance the bitplane decoding performance. Experimental results...
Performance Analysis of Iterative Decoding Algorithms for PEG LDPC Codes in Nakagami Fading Channels
Directory of Open Access Journals (Sweden)
O. Al Rasheed
2013-11-01
Full Text Available In this paper we give a comparative analysis of decoding algorithms of Low Density Parity Check (LDPC codes in a channel with the Nakagami distribution of the fading envelope. We consider the Progressive Edge-Growth (PEG method and Improved PEG method for the parity check matrix construction, which can be used to avoid short girths, small trapping sets and a high level of error floor. A comparative analysis of several classes of LDPC codes in various propagation conditions and decoded using different decoding algorithms is also presented.
Mapping of H.264 decoding on a multiprocessor architecture
van der Tol, Erik B.; Jaspers, Egbert G.; Gelderblom, Rob H.
2003-05-01
Due to the increasing significance of development costs in the competitive domain of high-volume consumer electronics, generic solutions are required to enable reuse of the design effort and to increase the potential market volume. As a result from this, Systems-on-Chip (SoCs) contain a growing amount of fully programmable media processing devices as opposed to application-specific systems, which offered the most attractive solutions due to a high performance density. The following motivates this trend. First, SoCs are increasingly dominated by their communication infrastructure and embedded memory, thereby making the cost of the functional units less significant. Moreover, the continuously growing design costs require generic solutions that can be applied over a broad product range. Hence, powerful programmable SoCs are becoming increasingly attractive. However, to enable power-efficient designs, that are also scalable over the advancing VLSI technology, parallelism should be fully exploited. Both task-level and instruction-level parallelism can be provided by means of e.g. a VLIW multiprocessor architecture. To provide the above-mentioned scalability, we propose to partition the data over the processors, instead of traditional functional partitioning. An advantage of this approach is the inherent locality of data, which is extremely important for communication-efficient software implementations. Consequently, a software implementation is discussed, enabling e.g. SD resolution H.264 decoding with a two-processor architecture, whereas High-Definition (HD) decoding can be achieved with an eight-processor system, executing the same software. Experimental results show that the data communication considerably reduces up to 65% directly improving the overall performance. Apart from considerable improvement in memory bandwidth, this novel concept of partitioning offers a natural approach for optimally balancing the load of all processors, thereby further improving the
Modeling task-specific neuronal ensembles improves decoding of grasp
Smith, Ryan J.; Soares, Alcimar B.; Rouse, Adam G.; Schieber, Marc H.; Thakor, Nitish V.
2018-06-01
Objective. Dexterous movement involves the activation and coordination of networks of neuronal populations across multiple cortical regions. Attempts to model firing of individual neurons commonly treat the firing rate as directly modulating with motor behavior. However, motor behavior may additionally be associated with modulations in the activity and functional connectivity of neurons in a broader ensemble. Accounting for variations in neural ensemble connectivity may provide additional information about the behavior being performed. Approach. In this study, we examined neural ensemble activity in primary motor cortex (M1) and premotor cortex (PM) of two male rhesus monkeys during performance of a center-out reach, grasp and manipulate task. We constructed point process encoding models of neuronal firing that incorporated task-specific variations in the baseline firing rate as well as variations in functional connectivity with the neural ensemble. Models were evaluated both in terms of their encoding capabilities and their ability to properly classify the grasp being performed. Main results. Task-specific ensemble models correctly predicted the performed grasp with over 95% accuracy and were shown to outperform models of neuronal activity that assume only a variable baseline firing rate. Task-specific ensemble models exhibited superior decoding performance in 82% of units in both monkeys (p < 0.01). Inclusion of ensemble activity also broadly improved the ability of models to describe observed spiking. Encoding performance of task-specific ensemble models, measured by spike timing predictability, improved upon baseline models in 62% of units. Significance. These results suggest that additional discriminative information about motor behavior found in the variations in functional connectivity of neuronal ensembles located in motor-related cortical regions is relevant to decode complex tasks such as grasping objects, and may serve the basis for more
Multiple-Symbol Decision-Feedback Space-Time Differential Decoding in Fading Channels
Directory of Open Access Journals (Sweden)
Wang Xiaodong
2002-01-01
Full Text Available Space-time differential coding (STDC is an effective technique for exploiting transmitter diversity while it does not require the channel state information at the receiver. However, like conventional differential modulation schemes, it exhibits an error floor in fading channels. In this paper, we develop an STDC decoding technique based on multiple-symbol detection and decision-feedback, which makes use of the second-order statistic of the fading processes and has a very low computational complexity. This decoding method can significantly lower the error floor of the conventional STDC decoding algorithm, especially in fast fading channels. The application of the proposed multiple-symbol decision-feedback STDC decoding technique in orthogonal frequency-division multiplexing (OFDM system is also discussed.
Gu, Yong; Angelaki, Dora E; DeAngelis, Gregory C
2014-07-01
Trial by trial covariations between neural activity and perceptual decisions (quantified by choice Probability, CP) have been used to probe the contribution of sensory neurons to perceptual decisions. CPs are thought to be determined by both selective decoding of neural activity and by the structure of correlated noise among neurons, but the respective roles of these factors in creating CPs have been controversial. We used biologically-constrained simulations to explore this issue, taking advantage of a peculiar pattern of CPs exhibited by multisensory neurons in area MSTd that represent self-motion. Although models that relied on correlated noise or selective decoding could both account for the peculiar pattern of CPs, predictions of the selective decoding model were substantially more consistent with various features of the neural and behavioral data. While correlated noise is essential to observe CPs, our findings suggest that selective decoding of neuronal signals also plays important roles.
A reduced complexity highly power/bandwidth efficient coded FQPSK system with iterative decoding
Simon, M. K.; Divsalar, D.
2001-01-01
Based on a representation of FQPSK as a trellis-coded modulation, this paper investigates the potential improvement in power efficiency obtained from the application of simple outer codes to form a concatenated coding arrangement with iterative decoding.
Feature reconstruction of LFP signals based on PLSR in the neural information decoding study.
Yonghui Dong; Zhigang Shang; Mengmeng Li; Xinyu Liu; Hong Wan
2017-07-01
To solve the problems of Signal-to-Noise Ratio (SNR) and multicollinearity when the Local Field Potential (LFP) signals is used for the decoding of animal motion intention, a feature reconstruction of LFP signals based on partial least squares regression (PLSR) in the neural information decoding study is proposed in this paper. Firstly, the feature information of LFP coding band is extracted based on wavelet transform. Then the PLSR model is constructed by the extracted LFP coding features. According to the multicollinearity characteristics among the coding features, several latent variables which contribute greatly to the steering behavior are obtained, and the new LFP coding features are reconstructed. Finally, the K-Nearest Neighbor (KNN) method is used to classify the reconstructed coding features to verify the decoding performance. The results show that the proposed method can achieve the highest accuracy compared to the other three methods and the decoding effect of the proposed method is robust.
DEFF Research Database (Denmark)
Keibler, Evan; Arumugam, Manimozhiyan; Brent, Michael R
2007-01-01
MOTIVATION: Hidden Markov models (HMMs) and generalized HMMs been successfully applied to many problems, but the standard Viterbi algorithm for computing the most probable interpretation of an input sequence (known as decoding) requires memory proportional to the length of the sequence, which can...... be prohibitive. Existing approaches to reducing memory usage either sacrifice optimality or trade increased running time for reduced memory. RESULTS: We developed two novel decoding algorithms, Treeterbi and Parallel Treeterbi, and implemented them in the TWINSCAN/N-SCAN gene-prediction system. The worst case...... asymptotic space and time are the same as for standard Viterbi, but in practice, Treeterbi optimally decodes arbitrarily long sequences with generalized HMMs in bounded memory without increasing running time. Parallel Treeterbi uses the same ideas to split optimal decoding across processors, dividing latency...
Zhang, Wuhong; Chen, Lixiang
2016-06-15
Digital spiral imaging has been demonstrated as an effective optical tool to encode optical information and retrieve topographic information of an object. Here we develop a conceptually new and concise scheme for optical image encoding and decoding toward free-space digital spiral imaging. We experimentally demonstrate that the optical lattices with ℓ=±50 orbital angular momentum superpositions and a clover image with nearly 200 Laguerre-Gaussian (LG) modes can be well encoded and successfully decoded. It is found that an image encoded/decoded with a two-index LG spectrum (considering both azimuthal and radial indices, ℓ and p) possesses much higher fidelity than that with a one-index LG spectrum (only considering the ℓ index). Our work provides an alternative tool for the image encoding/decoding scheme toward free-space optical communications.
Application of MTR soft-decision decoding in multiple-head ...
Indian Academy of Sciences (India)
basic MTR logic circuits, and to develop, a new one, the soft-decision MTR decoder, based on such ... of integrated circuits provides their quite simple realization. ..... recording channels, PSU-UNS International Conference on Engineering and ...
Optimal coding-decoding for systems controlled via a communication channel
Yi-wei, Feng; Guo, Ge
2013-12-01
In this article, we study the problem of controlling plants over a signal-to-noise ratio (SNR) constrained communication channel. Different from previous research, this article emphasises the importance of the actual channel model and coder/decoder in the study of network performance. Our major objectives include coder/decoder design for an additive white Gaussian noise (AWGN) channel with both standard network configuration and Youla parameter network architecture. We find that the optimal coder and decoder can be realised for different network configuration. The results are useful in determining the minimum channel capacity needed in order to stabilise plants over communication channels. The coder/decoder obtained can be used to analyse the effect of uncertainty on the channel capacity. An illustrative example is provided to show the effectiveness of the results.
Multiformat decoder for a DSP-based IP set-top box
Pescador, F.; Garrido, M. J.; Sanz, C.; Juárez, E.; Samper, D.; Antoniello, R.
2007-05-01
Internet Protocol Set-Top Boxes (IP STBs) based on single-processor architectures have been recently introduced in the market. In this paper, the implementation of an MPEG-4 SP/ASP video decoder for a multi-format IP STB based on a TMS320DM641 DSP is presented. An initial decoder for PC platform was fully tested and ported to the DSP. Using this code an optimization process was started achieving a 90% speedup. This process allows real-time MPEG-4 SP/ASP decoding. The MPEG-4 decoder has been integrated in an IP STB and tested in a real environment using DVD movies and TV channels with excellent results.
DS-OCDMA Encoder/Decoder Performance Analysis Using Optical Low-Coherence Reflectometry
Fsaifes, Ihsan; Lepers, Catherine; Obaton, Anne-Francoise; Gallion, Philippe
2006-08-01
Direct-sequence optical code-division multiple-access (DS-OCDMA) encoder/decoder based on sampled fiber Bragg gratings (S-FBGs) is characterized using phase-sensitive optical low-coherence reflectometry (OLCR). The OLCR technique allows localized measurements of FBG wavelength and physical length inside one S-FBG. This paper shows how the discrepancies between specifications and measurements of the different FBGs have some impact on spectral and temporal pulse responses of the OCDMA encoder/decoder. The FBG physical lengths lower than the specified ones are shown to affect the mean optical power reflected by the OCDMA encoder/decoder. The FBG wavelengths that are detuned from each other induce some modulations of S-FBG reflectivity resulting in encoder/decoder sensitivity to laser wavelength drift of the OCDMA system. Finally, highlighted by this OLCR study, some solutions to overcome limitations in performance with the S-FBG technology are suggested.
Identifying musical pieces from fMRI data using encoding and decoding models.
Hoefle, Sebastian; Engel, Annerose; Basilio, Rodrigo; Alluri, Vinoo; Toiviainen, Petri; Cagy, Maurício; Moll, Jorge
2018-02-02
Encoding models can reveal and decode neural representations in the visual and semantic domains. However, a thorough understanding of how distributed information in auditory cortices and temporal evolution of music contribute to model performance is still lacking in the musical domain. We measured fMRI responses during naturalistic music listening and constructed a two-stage approach that first mapped musical features in auditory cortices and then decoded novel musical pieces. We then probed the influence of stimuli duration (number of time points) and spatial extent (number of voxels) on decoding accuracy. Our approach revealed a linear increase in accuracy with duration and a point of optimal model performance for the spatial extent. We further showed that Shannon entropy is a driving factor, boosting accuracy up to 95% for music with highest information content. These findings provide key insights for future decoding and reconstruction algorithms and open new venues for possible clinical applications.
SWIPT in Multiuser MIMO Decode-and-Forward Relay Broadcasting Channel with Energy Harvesting Relays
Benkhelifa, Fatma; Salem, Ahmed Sultan; Alouini, Mohamed-Slim
2017-01-01
In this paper, we consider a multiuser multiple- input multiple-output (MIMO) decode-and-forward (DF) relay broadcasting channel (BC) with single source, multiple energy harvesting relays and multiple destinations. Since the end-to-end sum rate
Benkhelifa, Fatma; Salem, Ahmed Sultan; Alouini, Mohamed-Slim
2015-01-01
scenario where both the energy harvesting (EH) receiver and information decoding (ID) receiver at the relay have access to the whole received signal and its energy. The relay harvests the energy while receiving the signal from the source and uses
Hadamard upper bound on optimum joint decoding capacity of Wyner Gaussian cellular MAC
Shakir, Muhammad; Durrani, Tariq S; Alouini, Mohamed-Slim
2011-01-01
demonstrates that the analytical HUB based on the proposed approximation approach converges to the theoretical upper bound results in the medium to high signal to noise ratio regime and shows a reasonably tighter bound on optimum joint decoding capacity
Jointly-check iterative decoding algorithm for quantum sparse graph codes
International Nuclear Information System (INIS)
Jun-Hu, Shao; Bao-Ming, Bai; Wei, Lin; Lin, Zhou
2010-01-01
For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with a standard belief-propagation (BP) algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms the standard BP algorithm with an obvious performance improvement. (general)
LDPC code decoding adapted to the precoded partial response magnetic recording channels
International Nuclear Information System (INIS)
Lee, Jun; Kim, Kyuyong; Lee, Jaejin; Yang, Gijoo
2004-01-01
We propose a signal processing technique using LDPC (low-density parity-check) code instead of PRML (partial response maximum likelihood) system for the longitudinal magnetic recording channel. The scheme is designed by the precoder admitting level detection at the receiver-end and modifying the likelihood function for LDPC code decoding. The scheme can be collaborated with other decoder for turbo-like systems. The proposed algorithm can contribute to improve the performance of the conventional turbo-like systems
Decoding Individual Finger Movements from One Hand Using Human EEG Signals
Gonzalez, Jania; Ding, Lei
2014-01-01
Brain computer interface (BCI) is an assistive technology, which decodes neurophysiological signals generated by the human brain and translates them into control signals to control external devices, e.g., wheelchairs. One problem challenging noninvasive BCI technologies is the limited control dimensions from decoding movements of, mainly, large body parts, e.g., upper and lower limbs. It has been reported that complicated dexterous functions, i.e., finger movements, can be decoded in electrocorticography (ECoG) signals, while it remains unclear whether noninvasive electroencephalography (EEG) signals also have sufficient information to decode the same type of movements. Phenomena of broadband power increase and low-frequency-band power decrease were observed in EEG in the present study, when EEG power spectra were decomposed by a principal component analysis (PCA). These movement-related spectral structures and their changes caused by finger movements in EEG are consistent with observations in previous ECoG study, as well as the results from ECoG data in the present study. The average decoding accuracy of 77.11% over all subjects was obtained in classifying each pair of fingers from one hand using movement-related spectral changes as features to be decoded using a support vector machine (SVM) classifier. The average decoding accuracy in three epilepsy patients using ECoG data was 91.28% with the similarly obtained features and same classifier. Both decoding accuracies of EEG and ECoG are significantly higher than the empirical guessing level (51.26%) in all subjects (pEEG as in ECoG, and demonstrates the feasibility of discriminating finger movements from one hand using EEG. These findings are promising to facilitate the development of BCIs with rich control signals using noninvasive technologies. PMID:24416360
Zhang, Jianshu; Du, Jun; Dai, Lirong
2017-01-01
In this study, we present a novel end-to-end approach based on the encoder-decoder framework with the attention mechanism for online handwritten mathematical expression recognition (OHMER). First, the input two-dimensional ink trajectory information of handwritten expression is encoded via the gated recurrent unit based recurrent neural network (GRU-RNN). Then the decoder is also implemented by the GRU-RNN with a coverage-based attention model. The proposed approach can simultaneously accompl...
Euclidean Geometry Codes, minimum weight words and decodable error-patterns using bit-flipping
DEFF Research Database (Denmark)
Høholdt, Tom; Justesen, Jørn; Jonsson, Bergtor
2005-01-01
We determine the number of minimum wigth words in a class of Euclidean Geometry codes and link the performance of the bit-flipping decoding algorithm to the geometry of the error patterns.......We determine the number of minimum wigth words in a class of Euclidean Geometry codes and link the performance of the bit-flipping decoding algorithm to the geometry of the error patterns....
Decoder calibration with ultra small current sample set for intracortical brain-machine interface
Zhang, Peng; Ma, Xuan; Chen, Luyao; Zhou, Jin; Wang, Changyong; Li, Wei; He, Jiping
2018-04-01
Objective. Intracortical brain-machine interfaces (iBMIs) aim to restore efficient communication and movement ability for paralyzed patients. However, frequent recalibration is required for consistency and reliability, and every recalibration will require relatively large most current sample set. The aim in this study is to develop an effective decoder calibration method that can achieve good performance while minimizing recalibration time. Approach. Two rhesus macaques implanted with intracortical microelectrode arrays were trained separately on movement and sensory paradigm. Neural signals were recorded to decode reaching positions or grasping postures. A novel principal component analysis-based domain adaptation (PDA) method was proposed to recalibrate the decoder with only ultra small current sample set by taking advantage of large historical data, and the decoding performance was compared with other three calibration methods for evaluation. Main results. The PDA method closed the gap between historical and current data effectively, and made it possible to take advantage of large historical data for decoder recalibration in current data decoding. Using only ultra small current sample set (five trials of each category), the decoder calibrated using the PDA method could achieve much better and more robust performance in all sessions than using other three calibration methods in both monkeys. Significance. (1) By this study, transfer learning theory was brought into iBMIs decoder calibration for the first time. (2) Different from most transfer learning studies, the target data in this study were ultra small sample set and were transferred to the source data. (3) By taking advantage of historical data, the PDA method was demonstrated to be effective in reducing recalibration time for both movement paradigm and sensory paradigm, indicating a viable generalization. By reducing the demand for large current training data, this new method may facilitate the application
LDPC code decoding adapted to the precoded partial response magnetic recording channels
Energy Technology Data Exchange (ETDEWEB)
Lee, Jun E-mail: leejun28@sait.samsung.co.kr; Kim, Kyuyong; Lee, Jaejin; Yang, Gijoo
2004-05-01
We propose a signal processing technique using LDPC (low-density parity-check) code instead of PRML (partial response maximum likelihood) system for the longitudinal magnetic recording channel. The scheme is designed by the precoder admitting level detection at the receiver-end and modifying the likelihood function for LDPC code decoding. The scheme can be collaborated with other decoder for turbo-like systems. The proposed algorithm can contribute to improve the performance of the conventional turbo-like systems.
Sequence-to-Sequence Prediction of Vehicle Trajectory via LSTM Encoder-Decoder Architecture
Park, Seong Hyeon; Kim, ByeongDo; Kang, Chang Mook; Chung, Chung Choo; Choi, Jun Won
2018-01-01
In this paper, we propose a deep learning based vehicle trajectory prediction technique which can generate the future trajectory sequence of surrounding vehicles in real time. We employ the encoder-decoder architecture which analyzes the pattern underlying in the past trajectory using the long short-term memory (LSTM) based encoder and generates the future trajectory sequence using the LSTM based decoder. This structure produces the $K$ most likely trajectory candidates over occupancy grid ma...
Distributed-phase OCDMA encoder-decoders based on fiber Bragg gratings
Zhang, Zhaowei; Tian, C.; Petropoulos, P.; Richardson, D.J.; Ibsen, M.
2007-01-01
We propose and demonstrate new optical code-division multiple-access (OCDMA) encoder-decoders having a continuous phase-distribution. With the same spatial refractive index distribution as the reconfigurable optical phase encoder-decoders, they are inherently suitable for the application in reconfigurable OCDMA systems. Furthermore, compared with conventional discrete-phase devices, they also have additional advantages of being more tolerant to input pulse width and, therefore, have the poten...
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Naotsugu Tsuchiya
Full Text Available Faces are processed by a neural system with distributed anatomical components, but the roles of these components remain unclear. A dominant theory of face perception postulates independent representations of invariant aspects of faces (e.g., identity in ventral temporal cortex including the fusiform gyrus, and changeable aspects of faces (e.g., emotion in lateral temporal cortex including the superior temporal sulcus. Here we recorded neuronal activity directly from the cortical surface in 9 neurosurgical subjects undergoing epilepsy monitoring while they viewed static and dynamic facial expressions. Applying novel decoding analyses to the power spectrogram of electrocorticograms (ECoG from over 100 contacts in ventral and lateral temporal cortex, we found better representation of both invariant and changeable aspects of faces in ventral than lateral temporal cortex. Critical information for discriminating faces from geometric patterns was carried by power modulations between 50 to 150 Hz. For both static and dynamic face stimuli, we obtained a higher decoding performance in ventral than lateral temporal cortex. For discriminating fearful from happy expressions, critical information was carried by power modulation between 60-150 Hz and below 30 Hz, and again better decoded in ventral than lateral temporal cortex. Task-relevant attention improved decoding accuracy more than 10% across a wide frequency range in ventral but not at all in lateral temporal cortex. Spatial searchlight decoding showed that decoding performance was highest around the middle fusiform gyrus. Finally, we found that the right hemisphere, in general, showed superior decoding to the left hemisphere. Taken together, our results challenge the dominant model for independent face representation of invariant and changeable aspects: information about both face attributes was better decoded from a single region in the middle fusiform gyrus.
Cascading Oscillators in Decoding Speech: Reflection of a Cortical Computation Principle
2016-09-06
purely) auditory or articulatory model can explain this behavior. The insertion of gaps was interpreted as the act of providing extra decoding time...The windows are generated by a segmentation process, implemented by an array of cascaded oscillators. Correct segmentation is a critical...prerequisite for correct decoding, and segmentation is correct as long as the oscillators successfully track the input rhythms. Syllabic segmentation utilizes
How Major Depressive Disorder affects the ability to decode multimodal dynamic emotional stimuli
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FILOMENA SCIBELLI
2016-09-01
Full Text Available Most studies investigating the processing of emotions in depressed patients reported impairments in the decoding of negative emotions. However, these studies adopted static stimuli (mostly stereotypical facial expressions corresponding to basic emotions which do not reflect the way people experience emotions in everyday life. For this reason, this work proposes to investigate the decoding of emotional expressions in patients affected by Recurrent Major Depressive Disorder (RMDDs using dynamic audio/video stimuli. RMDDs’ performance is compared with the performance of patients with Adjustment Disorder with Depressed Mood (ADs and healthy (HCs subjects. The experiments involve 27 RMDDs (16 with acute depression - RMDD-A, and 11 in a compensation phase - RMDD-C, 16 ADs and 16 HCs. The ability to decode emotional expressions is assessed through an emotion recognition task based on short audio (without video, video (without audio and audio/video clips. The results show that AD patients are significantly less accurate than HCs in decoding fear, anger, happiness, surprise and sadness. RMDD-As with acute depression are significantly less accurate than HCs in decoding happiness, sadness and surprise. Finally, no significant differences were found between HCs and RMDD-Cs in a compensation phase. The different communication channels and the types of emotion play a significant role in limiting the decoding accuracy.
A lossy graph model for delay reduction in generalized instantly decodable network coding
Douik, Ahmed S.
2014-06-01
The problem of minimizing the decoding delay in Generalized instantly decodable network coding (G-IDNC) for both perfect and lossy feedback scenarios is formulated as a maximum weight clique problem over the G-IDNC graph in. In this letter, we introduce a new lossy G-IDNC graph (LG-IDNC) model to further minimize the decoding delay in lossy feedback scenarios. Whereas the G-IDNC graph represents only doubtless combinable packets, the LG-IDNC graph represents also uncertain packet combinations, arising from lossy feedback events, when the expected decoding delay of XORing them among themselves or with other certain packets is lower than that expected when sending these packets separately. We compare the decoding delay performance of LG-IDNC and G-IDNC graphs through extensive simulations. Numerical results show that our new LG-IDNC graph formulation outperforms the G-IDNC graph formulation in all lossy feedback situations and achieves significant improvement in the decoding delay especially when the feedback erasure probability is higher than the packet erasure probability. © 2012 IEEE.
Online decoding of object-based attention using real-time fMRI.
Niazi, Adnan M; van den Broek, Philip L C; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; van Gerven, Marcel A J
2014-01-01
Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Word Decoding Development during Phonics Instruction in Children at Risk for Dyslexia.
Schaars, Moniek M H; Segers, Eliane; Verhoeven, Ludo
2017-05-01
In the present study, we examined the early word decoding development of 73 children at genetic risk of dyslexia and 73 matched controls. We conducted monthly curriculum-embedded word decoding measures during the first 5 months of phonics-based reading instruction followed by standardized word decoding measures halfway and by the end of first grade. In kindergarten, vocabulary, phonological awareness, lexical retrieval, and verbal and visual short-term memory were assessed. The results showed that the children at risk were less skilled in phonemic awareness in kindergarten. During the first 5 months of reading instruction, children at risk were less efficient in word decoding and the discrepancy increased over the months. In subsequent months, the discrepancy prevailed for simple words but increased for more complex words. Phonemic awareness and lexical retrieval predicted the reading development in children at risk and controls to the same extent. It is concluded that children at risk are behind their typical peers in word decoding development starting from the very beginning. Furthermore, it is concluded that the disadvantage increased during phonics instruction and that the same predictors underlie the development of word decoding in the two groups of children. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Complexity Analysis of Reed-Solomon Decoding over GF(2m without Using Syndromes
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Zhiyuan Yan
2008-06-01
Full Text Available There has been renewed interest in decoding Reed-Solomon (RS codes without using syndromes recently. In this paper, we investigate the complexity of syndromeless decoding, and compare it to that of syndrome-based decoding. Aiming to provide guidelines to practical applications, our complexity analysis focuses on RS codes over characteristic-2 fields, for which some multiplicative FFT techniques are not applicable. Due to moderate block lengths of RS codes in practice, our analysis is complete, without big O notation. In addition to fast implementation using additive FFT techniques, we also consider direct implementation, which is still relevant for RS codes with moderate lengths. For high-rate RS codes, when compared to syndrome-based decoding algorithms, not only syndromeless decoding algorithms require more field operations regardless of implementation, but also decoder architectures based on their direct implementations have higher hardware costs and lower throughput. We also derive tighter bounds on the complexities of fast polynomial multiplications based on Cantor's approach and the fast extended Euclidean algorithm.
Design and Analysis of Adaptive Message Coding on LDPC Decoder with Faulty Storage
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Guangjun Ge
2018-01-01
Full Text Available Unreliable message storage severely degrades the performance of LDPC decoders. This paper discusses the impacts of message errors on LDPC decoders and schemes improving the robustness. Firstly, we develop a discrete density evolution analysis for faulty LDPC decoders, which indicates that protecting the sign bits of messages is effective enough for finite-precision LDPC decoders. Secondly, we analyze the effects of quantization precision loss for static sign bit protection and propose an embedded dynamic coding scheme by adaptively employing the least significant bits (LSBs to protect the sign bits. Thirdly, we give a construction of Hamming product code for the adaptive coding and present low complexity decoding algorithms. Theoretic analysis indicates that the proposed scheme outperforms traditional triple modular redundancy (TMR scheme in decoding both threshold and residual errors, while Monte Carlo simulations show that the performance loss is less than 0.2 dB when the storage error probability varies from 10-3 to 10-4.
Techniques and Architectures for Hazard-Free Semi-Parallel Decoding of LDPC Codes
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Rovini Massimo
2009-01-01
Full Text Available The layered decoding algorithm has recently been proposed as an efficient means for the decoding of low-density parity-check (LDPC codes, thanks to the remarkable improvement in the convergence speed (2x of the decoding process. However, pipelined semi-parallel decoders suffer from violations or "hazards" between consecutive updates, which not only violate the layered principle but also enforce the loops in the code, thus spoiling the error correction performance. This paper describes three different techniques to properly reschedule the decoding updates, based on the careful insertion of "idle" cycles, to prevent the hazards of the pipeline mechanism. Also, different semi-parallel architectures of a layered LDPC decoder suitable for use with such techniques are analyzed. Then, taking the LDPC codes for the wireless local area network (IEEE 802.11n as a case study, a detailed analysis of the performance attained with the proposed techniques and architectures is reported, and results of the logic synthesis on a 65 nm low-power CMOS technology are shown.
Complexity Analysis of Reed-Solomon Decoding over GF without Using Syndromes
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Chen Ning
2008-01-01
Full Text Available Abstract There has been renewed interest in decoding Reed-Solomon (RS codes without using syndromes recently. In this paper, we investigate the complexity of syndromeless decoding, and compare it to that of syndrome-based decoding. Aiming to provide guidelines to practical applications, our complexity analysis focuses on RS codes over characteristic-2 fields, for which some multiplicative FFT techniques are not applicable. Due to moderate block lengths of RS codes in practice, our analysis is complete, without big notation. In addition to fast implementation using additive FFT techniques, we also consider direct implementation, which is still relevant for RS codes with moderate lengths. For high-rate RS codes, when compared to syndrome-based decoding algorithms, not only syndromeless decoding algorithms require more field operations regardless of implementation, but also decoder architectures based on their direct implementations have higher hardware costs and lower throughput. We also derive tighter bounds on the complexities of fast polynomial multiplications based on Cantor's approach and the fast extended Euclidean algorithm.
Efficient decoding with steady-state Kalman filter in neural interface systems.
Malik, Wasim Q; Truccolo, Wilson; Brown, Emery N; Hochberg, Leigh R
2011-02-01
The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics. We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5±0.5 s (mean ±s.d.). The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25±3 single units by a factor of 7.0±0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.
Delay reduction in lossy intermittent feedback for generalized instantly decodable network coding
Douik, Ahmed S.; Sorour, Sameh; Alouini, Mohamed-Slim; Ai-Naffouri, Tareq Y.
2013-01-01
In this paper, we study the effect of lossy intermittent feedback loss events on the multicast decoding delay performance of generalized instantly decodable network coding. These feedback loss events create uncertainty at the sender about the reception statues of different receivers and thus uncertainty to accurately determine subsequent instantly decodable coded packets. To solve this problem, we first identify the different possibilities of uncertain packets at the sender and their probabilities. We then derive the expression of the mean decoding delay. We formulate the Generalized Instantly Decodable Network Coding (G-IDNC) minimum decoding delay problem as a maximum weight clique problem. Since finding the optimal solution is NP-hard, we design a variant of the algorithm employed in [1]. Our algorithm is compared to the two blind graph update proposed in [2] through extensive simulations. Results show that our algorithm outperforms the blind approaches in all the situations and achieves a tolerable degradation, against the perfect feedback, for large feedback loss period. © 2013 IEEE.
Delay reduction in lossy intermittent feedback for generalized instantly decodable network coding
Douik, Ahmed S.
2013-10-01
In this paper, we study the effect of lossy intermittent feedback loss events on the multicast decoding delay performance of generalized instantly decodable network coding. These feedback loss events create uncertainty at the sender about the reception statues of different receivers and thus uncertainty to accurately determine subsequent instantly decodable coded packets. To solve this problem, we first identify the different possibilities of uncertain packets at the sender and their probabilities. We then derive the expression of the mean decoding delay. We formulate the Generalized Instantly Decodable Network Coding (G-IDNC) minimum decoding delay problem as a maximum weight clique problem. Since finding the optimal solution is NP-hard, we design a variant of the algorithm employed in [1]. Our algorithm is compared to the two blind graph update proposed in [2] through extensive simulations. Results show that our algorithm outperforms the blind approaches in all the situations and achieves a tolerable degradation, against the perfect feedback, for large feedback loss period. © 2013 IEEE.
Utilizing Cross-Layer Information to Improve Performance in JPEG2000 Decoding
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Hannes Persson
2007-01-01
Full Text Available We focus on wireless multimedia communication and investigate how cross-layer information can be used to improve performance at the application layer, using JPEG2000 as an example. The cross-layer information is in the form of soft information from the physical layer. The soft information, which is supplied by a soft decision demodulator, yields reliability measures for the received bits and is fed into two soft input iterative JPEG2000 image decoders. When errors are detected with the error detecting mechanisms in JPEG2000, the decoders utilize the soft information to point out likely transmission errors. Hence, the decoders can correct errors and increase the image quality without making time-consuming retransmissions. We believe that the proposed decoding method utilizing soft information is suitable for a general IP-based network and that it keeps the principles of a layered structure of the protocol stack intact. Further, experimental results with images transmitted over a simulated wireless channel show that a simple decoding algorithm that utilizes soft information can give high gains in image quality compared to the standard hard-decision decoding.
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Vito De Feo
2017-05-01
Full Text Available Brain-machine interfaces (BMIs promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.
De Feo, Vito; Boi, Fabio; Safaai, Houman; Onken, Arno; Panzeri, Stefano; Vato, Alessandro
2017-01-01
Brain-machine interfaces (BMIs) promise to improve the quality of life of patients suffering from sensory and motor disabilities by creating a direct communication channel between the brain and the external world. Yet, their performance is currently limited by the relatively small amount of information that can be decoded from neural activity recorded form the brain. We have recently proposed that such decoding performance may be improved when using state-dependent decoding algorithms that predict and discount the large component of the trial-to-trial variability of neural activity which is due to the dependence of neural responses on the network's current internal state. Here we tested this idea by using a bidirectional BMI to investigate the gain in performance arising from using a state-dependent decoding algorithm. This BMI, implemented in anesthetized rats, controlled the movement of a dynamical system using neural activity decoded from motor cortex and fed back to the brain the dynamical system's position by electrically microstimulating somatosensory cortex. We found that using state-dependent algorithms that tracked the dynamics of ongoing activity led to an increase in the amount of information extracted form neural activity by 22%, with a consequently increase in all of the indices measuring the BMI's performance in controlling the dynamical system. This suggests that state-dependent decoding algorithms may be used to enhance BMIs at moderate computational cost.
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Johann A. Briffa
2014-06-01
Full Text Available In this study, the authors consider time-varying block (TVB codes, which generalise a number of previous synchronisation error-correcting codes. They also consider various practical issues related to maximum a posteriori (MAP decoding of these codes. Specifically, they give an expression for the expected distribution of drift between transmitter and receiver because of synchronisation errors. They determine an appropriate choice for state space limits based on the drift probability distribution. In turn, they obtain an expression for the decoder complexity under given channel conditions in terms of the state space limits used. For a given state space, they also give a number of optimisations that reduce the algorithm complexity with no further loss of decoder performance. They also show how the MAP decoder can be used in the absence of known frame boundaries, and demonstrate that an appropriate choice of decoder parameters allows the decoder to approach the performance when frame boundaries are known, at the expense of some increase in complexity. Finally, they express some existing constructions as TVB codes, comparing performance with published results and showing that improved performance is possible by taking advantage of the flexibility of TVB codes.
Khorasani, Abed; Heydari Beni, Nargess; Shalchyan, Vahid; Daliri, Mohammad Reza
2016-10-21
Local field potential (LFP) signals recorded by intracortical microelectrodes implanted in primary motor cortex can be used as a high informative input for decoding of motor functions. Recent studies show that different kinematic parameters such as position and velocity can be inferred from multiple LFP signals as precisely as spiking activities, however, continuous decoding of the force magnitude from the LFP signals in freely moving animals has remained an open problem. Here, we trained three rats to press a force sensor for getting a drop of water as a reward. A 16-channel micro-wire array was implanted in the primary motor cortex of each trained rat, and obtained LFP signals were used for decoding of the continuous values recorded by the force sensor. Average coefficient of correlation and the coefficient of determination between decoded and actual force signals were r = 0.66 and R 2 = 0.42, respectively. We found that LFP signal on gamma frequency bands (30-120 Hz) had the most contribution in the trained decoding model. This study suggests the feasibility of using low number of LFP channels for the continuous force decoding in freely moving animals resembling BMI systems in real life applications.
Abediseid, Walid
2012-12-21
The exact average complexity analysis of the basic sphere decoder for general space-time codes applied to multiple-input multiple-output (MIMO) wireless channel is known to be difficult. In this work, we shed the light on the computational complexity of sphere decoding for the quasi- static, lattice space-time (LAST) coded MIMO channel. Specifically, we drive an upper bound of the tail distribution of the decoder\\'s computational complexity. We show that when the computational complexity exceeds a certain limit, this upper bound becomes dominated by the outage probability achieved by LAST coding and sphere decoding schemes. We then calculate the minimum average computational complexity that is required by the decoder to achieve near optimal performance in terms of the system parameters. Our results indicate that there exists a cut-off rate (multiplexing gain) for which the average complexity remains bounded. Copyright © 2012 John Wiley & Sons, Ltd.
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Liu Yu-Sun
2011-01-01
Full Text Available Abstract The performance of the wrap-around Viterbi decoding algorithm with finite truncation depth and fixed decoding trellis length is investigated for tail-biting convolutional codes in the mobile WiMAX standard. Upper bounds on the error probabilities induced by finite truncation depth and the uncertainty of the initial state are derived for the AWGN channel. The truncation depth and the decoding trellis length that yield negligible performance loss are obtained for all transmission rates over the Rayleigh channel using computer simulations. The results show that the circular decoding algorithm with an appropriately chosen truncation depth and a decoding trellis just a fraction longer than the original received code words can achieve almost the same performance as the optimal maximum likelihood decoding algorithm in mobile WiMAX. A rule of thumb for the values of the truncation depth and the trellis tail length is also proposed.
The locking-decoding frontier for generic dynamics.
Dupuis, Frédéric; Florjanczyk, Jan; Hayden, Patrick; Leung, Debbie
2013-11-08
It is known that the maximum classical mutual information, which can be achieved between measurements on pairs of quantum systems, can drastically underestimate the quantum mutual information between them. In this article, we quantify this distinction between classical and quantum information by demonstrating that after removing a logarithmic-sized quantum system from one half of a pair of perfectly correlated bitstrings, even the most sensitive pair of measurements might yield only outcomes essentially independent of each other. This effect is a form of information locking but the definition we use is strictly stronger than those used previously. Moreover, we find that this property is generic, in the sense that it occurs when removing a random subsystem. As such, the effect might be relevant to statistical mechanics or black hole physics. While previous works had always assumed a uniform message, we assume only a min-entropy bound and also explore the effect of entanglement. We find that classical information is strongly locked almost until it can be completely decoded. Finally, we exhibit a quantum key distribution protocol that is 'secure' in the sense of accessible information but in which leakage of even a logarithmic number of bits compromises the secrecy of all others.
Decoding the auditory brain with canonical component analysis.
de Cheveigné, Alain; Wong, Daniel D E; Di Liberto, Giovanni M; Hjortkjær, Jens; Slaney, Malcolm; Lalor, Edmund
2018-05-15
The relation between a stimulus and the evoked brain response can shed light on perceptual processes within the brain. Signals derived from this relation can also be harnessed to control external devices for Brain Computer Interface (BCI) applications. While the classic event-related potential (ERP) is appropriate for isolated stimuli, more sophisticated "decoding" strategies are needed to address continuous stimuli such as speech, music or environmental sounds. Here we describe an approach based on Canonical Correlation Analysis (CCA) that finds the optimal transform to apply to both the stimulus and the response to reveal correlations between the two. Compared to prior methods based on forward or backward models for stimulus-response mapping, CCA finds significantly higher correlation scores, thus providing increased sensitivity to relatively small effects, and supports classifier schemes that yield higher classification scores. CCA strips the brain response of variance unrelated to the stimulus, and the stimulus representation of variance that does not affect the response, and thus improves observations of the relation between stimulus and response. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
Ratiometric Decoding of Pheromones for a Biomimetic Infochemical Communication System
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Guangfen Wei
2017-10-01
Full Text Available Biosynthetic infochemical communication is an emerging scientific field employing molecular compounds for information transmission, labelling, and biochemical interfacing; having potential application in diverse areas ranging from pest management to group coordination of swarming robots. Our communication system comprises a chemoemitter module that encodes information by producing volatile pheromone components and a chemoreceiver module that decodes the transmitted ratiometric information via polymer-coated piezoelectric Surface Acoustic Wave Resonator (SAWR sensors. The inspiration for such a system is based on the pheromone-based communication between insects. Ten features are extracted from the SAWR sensor response and analysed using multi-variate classification techniques, i.e., Linear Discriminant Analysis (LDA, Probabilistic Neural Network (PNN, and Multilayer Perception Neural Network (MLPNN methods, and an optimal feature subset is identified. A combination of steady state and transient features of the sensor signals showed superior performances with LDA and MLPNN. Although MLPNN gave excellent results reaching 100% recognition rate at 400 s, over all time stations PNN gave the best performance based on an expanded data-set with adjacent neighbours. In this case, 100% of the pheromone mixtures were successfully identified just 200 s after they were first injected into the wind tunnel. We believe that this approach can be used for future chemical communication employing simple mixtures of airborne molecules.
Ayala, Sandra M
2010-01-01
Ten first grade students, participating in a Tier II response to intervention (RTI) reading program received an intervention of video self modeling to improve decoding skills and sight word recognition. The students were video recorded blending and segmenting decodable words, and reading sight words taken directly from their curriculum instruction. Individual videos were recorded and edited to show students successfully and accurately decoding words and practicing sight word recognition. Each...
Hardware Implementation of A Non-RLL Soft-decoding Beacon-based Visible Light Communication Receiver
Nguyen, Duc-Phuc; Le, Dinh-Dung; Tran, Thi-Hong; Huynh, Huu-Thuan; Nakashima, Yasuhiko
2018-01-01
Visible light communication (VLC)-based beacon systems, which usually transmit identification (ID) information in small-size data frames are applied widely in indoor localization applications. There is one fact that flicker of LED light should be avoid in any VLC systems. Current flicker mitigation solutions based on run-length limited (RLL) codes suffer from reduced code rates, or are limited to hard-decoding forward error correction (FEC) decoders. Recently, soft-decoding techniques of RLL-...
Yoles-Frenkel, Michal; Kahan, Anat; Ben-Shaul, Yoram
2018-05-23
The vomeronasal system (VNS) is a major vertebrate chemosensory system that functions in parallel to the main olfactory system (MOS). Despite many similarities, the two systems dramatically differ in the temporal domain. While MOS responses are governed by breathing and follow a subsecond temporal scale, VNS responses are uncoupled from breathing and evolve over seconds. This suggests that the contribution of response dynamics to stimulus information will differ between these systems. While temporal dynamics in the MOS are widely investigated, similar analyses in the accessory olfactory bulb (AOB) are lacking. Here, we have addressed this issue using controlled stimulus delivery to the vomeronasal organ of male and female mice. We first analyzed the temporal properties of AOB projection neurons and demonstrated that neurons display prolonged, variable, and neuron-specific characteristics. We then analyzed various decoding schemes using AOB population responses. We showed that compared with the simplest scheme (i.e., integration of spike counts over the entire response period), the division of this period into smaller temporal bins actually yields poorer decoding accuracy. However, optimal classification accuracy can be achieved well before the end of the response period by integrating spike counts within temporally defined windows. Since VNS stimulus uptake is variable, we analyzed decoding using limited information about stimulus uptake time, and showed that with enough neurons, such time-invariant decoding is feasible. Finally, we conducted simulations that demonstrated that, unlike the main olfactory bulb, the temporal features of AOB neurons disfavor decoding with high temporal accuracy, and, rather, support decoding without precise knowledge of stimulus uptake time. SIGNIFICANCE STATEMENT A key goal in sensory system research is to identify which metrics of neuronal activity are relevant for decoding stimulus features. Here, we describe the first systematic
Directory of Open Access Journals (Sweden)
Edouard Gentaz
Full Text Available Based on the assumption that good decoding skills constitute a bootstrapping mechanism for reading comprehension, the present study investigated the relative contribution of the former skill to the latter compared to that of three other predictors of reading comprehension (listening comprehension, vocabulary and phonemic awareness in 392 French-speaking first graders from low SES families. This large sample was split into three groups according to their level of decoding skills assessed by pseudoword reading. Using a cutoff of 1 SD above or below the mean of the entire population, there were 63 good decoders, 267 average decoders and 62 poor decoders. 58% of the variance in reading comprehension was explained by our four predictors, with decoding skills proving to be the best predictor (12.1%, 7.3% for listening comprehension, 4.6% for vocabulary and 3.3% for phonemic awareness. Interaction between group versus decoding skills, listening comprehension and phonemic awareness accounted for significant additional variance (3.6%, 1.1% and 1.0%, respectively. The effects on reading comprehension of decoding skills and phonemic awareness were higher in poor and average decoders than in good decoders whereas listening comprehension accounted for more variance in good and average decoders than in poor decoders. Furthermore, the percentage of children with impaired reading comprehension skills was higher in the group of poor decoders (55% than in the two other groups (average decoders: 7%; good decoders: 0% and only 6 children (1.5% had impaired reading comprehension skills with unimpaired decoding skills, listening comprehension or vocabulary. These results challenge the outcomes of studies on "poor comprehenders" by showing that, at least in first grade, poor reading comprehension is strongly linked to the level of decoding skills.
Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection
Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang
2018-01-01
In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10−5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced. PMID:29342963
High-speed architecture for the decoding of trellis-coded modulation
Osborne, William P.
1992-01-01
Since 1971, when the Viterbi Algorithm was introduced as the optimal method of decoding convolutional codes, improvements in circuit technology, especially VLSI, have steadily increased its speed and practicality. Trellis-Coded Modulation (TCM) combines convolutional coding with higher level modulation (non-binary source alphabet) to provide forward error correction and spectral efficiency. For binary codes, the current stare-of-the-art is a 64-state Viterbi decoder on a single CMOS chip, operating at a data rate of 25 Mbps. Recently, there has been an interest in increasing the speed of the Viterbi Algorithm by improving the decoder architecture, or by reducing the algorithm itself. Designs employing new architectural techniques are now in existence, however these techniques are currently applied to simpler binary codes, not to TCM. The purpose of this report is to discuss TCM architectural considerations in general, and to present the design, at the logic gate level, or a specific TCM decoder which applies these considerations to achieve high-speed decoding.
Decoding DNA labels by melting curve analysis using real-time PCR.
Balog, József A; Fehér, Liliána Z; Puskás, László G
2017-12-01
Synthetic DNA has been used as an authentication code for a diverse number of applications. However, existing decoding approaches are based on either DNA sequencing or the determination of DNA length variations. Here, we present a simple alternative protocol for labeling different objects using a small number of short DNA sequences that differ in their melting points. Code amplification and decoding can be done in two steps using quantitative PCR (qPCR). To obtain a DNA barcode with high complexity, we defined 8 template groups, each having 4 different DNA templates, yielding 158 (>2.5 billion) combinations of different individual melting temperature (Tm) values and corresponding ID codes. The reproducibility and specificity of the decoding was confirmed by using the most complex template mixture, which had 32 different products in 8 groups with different Tm values. The industrial applicability of our protocol was also demonstrated by labeling a drone with an oil-based paint containing a predefined DNA code, which was then successfully decoded. The method presented here consists of a simple code system based on a small number of synthetic DNA sequences and a cost-effective, rapid decoding protocol using a few qPCR reactions, enabling a wide range of authentication applications.
Decoding visual object categories from temporal correlations of ECoG signals.
Majima, Kei; Matsuo, Takeshi; Kawasaki, Keisuke; Kawai, Kensuke; Saito, Nobuhito; Hasegawa, Isao; Kamitani, Yukiyasu
2014-04-15
How visual object categories are represented in the brain is one of the key questions in neuroscience. Studies on low-level visual features have shown that relative timings or phases of neural activity between multiple brain locations encode information. However, whether such temporal patterns of neural activity are used in the representation of visual objects is unknown. Here, we examined whether and how visual object categories could be predicted (or decoded) from temporal patterns of electrocorticographic (ECoG) signals from the temporal cortex in five patients with epilepsy. We used temporal correlations between electrodes as input features, and compared the decoding performance with features defined by spectral power and phase from individual electrodes. While using power or phase alone, the decoding accuracy was significantly better than chance, correlations alone or those combined with power outperformed other features. Decoding performance with correlations was degraded by shuffling the order of trials of the same category in each electrode, indicating that the relative time series between electrodes in each trial is critical. Analysis using a sliding time window revealed that decoding performance with correlations began to rise earlier than that with power. This earlier increase in performance was replicated by a model using phase differences to encode categories. These results suggest that activity patterns arising from interactions between multiple neuronal units carry additional information on visual object categories. Copyright © 2013 Elsevier Inc. All rights reserved.
Kim, Yong-Hee; Thakor, Nitish V; Schieber, Marc H; Kim, Hyoung-Nam
2015-05-01
Future generations of brain-machine interface (BMI) will require more dexterous motion control such as hand and finger movements. Since a population of neurons in the primary motor cortex (M1) area is correlated with finger movements, neural activities recorded in M1 area are used to reconstruct an intended finger movement. In a BMI system, decoding discrete finger movements from a large number of input neurons does not guarantee a higher decoding accuracy in spite of the increase in computational burden. Hence, we hypothesize that selecting neurons important for coding dexterous flexion/extension of finger movements would improve the BMI performance. In this paper, two metrics are presented to quantitatively measure the importance of each neuron based on Bayes risk minimization and deflection coefficient maximization in a statistical decision problem. Since motor cortical neurons are active with movements of several different fingers, the proposed method is more suitable for a discrete decoding of flexion-extension finger movements than the previous methods for decoding reaching movements. In particular, the proposed metrics yielded high decoding accuracies across all subjects and also in the case of including six combined two-finger movements. While our data acquisition and analysis was done off-line and post processing, our results point to the significance of highly coding neurons in improving BMI performance.
Douik, Ahmed S.
2015-11-05
This paper considers the multicast decoding delay reduction problem for generalized instantly decodable network coding (G-IDNC) over persistent erasure channels with feedback imperfections. The feedback scenario discussed is the most general situation in which the sender does not always receive acknowledgments from the receivers after each transmission and the feedback communications are subject to loss. The decoding delay increment expressions are derived and employed to express the decoding delay reduction problem as a maximum weight clique problem in the G-IDNC graph. This paper provides a theoretical analysis of the expected decoding delay increase at each time instant. Problem formulations in simpler channel and feedback models are shown to be special cases of the proposed generalized formulation. Since finding the optimal solution to the problem is known to be NP-hard, a suboptimal greedy algorithm is designed and compared with blind approaches proposed in the literature. Through extensive simulations, the proposed algorithm is shown to outperform the blind methods in all situations and to achieve significant improvement, particularly for high time-correlated channels.
Scaffolding Students’ Independent Decoding of Unfamiliar Text with a Prototype of an eBook-feature
Directory of Open Access Journals (Sweden)
Stig T Gissel
2015-10-01
Full Text Available This study was undertaken to design, evaluate and refine an eBook-feature that supports students’ decoding of unfamiliar text. The feature supports students’ independent reading of eBooks with text-to-speech, graded support in the form of syllabification and rhyme analogy, and by dividing the word material into different categories based on the frequency and regularity of the word or its constituent parts. The eBook-feature is based on connectionist models of reading and reading acquisition and the theory of scaffolding. Students are supported in mapping between spelling and sound, in identifying the relevant spelling patterns and in generalizing, in order to strengthen their decoding skills. The prototype was evaluated with Danish students in the second grade to see how and under what circumstances students can use the feature in ways that strengthen their decoding skills and support them in reading unfamiliar text. It was found that most students could interact with the eBook-material in ways that the envisioned learning trajectory in the study predicts are beneficial in strengthening their decoding skills. The study contributes with both principles for designing digital learning material with supportive features for decoding unfamiliar text and with a concrete proposal for a design. The perspectives for making reading acquisition more differentiated and meaningful for second graders in languages with irregular spelling are discussed.
Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision.
Wen, Haiguang; Shi, Junxing; Zhang, Yizhen; Lu, Kun-Han; Cao, Jiayue; Liu, Zhongming
2017-10-20
Convolutional neural network (CNN) driven by image recognition has been shown to be able to explain cortical responses to static pictures at ventral-stream areas. Here, we further showed that such CNN could reliably predict and decode functional magnetic resonance imaging data from humans watching natural movies, despite its lack of any mechanism to account for temporal dynamics or feedback processing. Using separate data, encoding and decoding models were developed and evaluated for describing the bi-directional relationships between the CNN and the brain. Through the encoding models, the CNN-predicted areas covered not only the ventral stream, but also the dorsal stream, albeit to a lesser degree; single-voxel response was visualized as the specific pixel pattern that drove the response, revealing the distinct representation of individual cortical location; cortical activation was synthesized from natural images with high-throughput to map category representation, contrast, and selectivity. Through the decoding models, fMRI signals were directly decoded to estimate the feature representations in both visual and semantic spaces, for direct visual reconstruction and semantic categorization, respectively. These results corroborate, generalize, and extend previous findings, and highlight the value of using deep learning, as an all-in-one model of the visual cortex, to understand and decode natural vision. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Directory of Open Access Journals (Sweden)
Mohammad S. Islam
2017-01-01
Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.
Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection.
Meng, Jiahui; Zhao, Danfeng; Tian, Hai; Zhang, Liang
2018-01-15
In order to improve the performance of non-binary low-density parity check codes (LDPC) hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA) and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes' (VN) magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF) algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER) of 10 -5 over an additive white Gaussian noise (AWGN) channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.
Analysis of error floor of LDPC codes under LP decoding over the BSC
Energy Technology Data Exchange (ETDEWEB)
Chertkov, Michael [Los Alamos National Laboratory; Chilappagari, Shashi [UNIV OF AZ; Vasic, Bane [UNIV OF AZ; Stepanov, Mikhail [UNIV OF AZ
2009-01-01
We consider linear programming (LP) decoding of a fixed low-density parity-check (LDPC) code over the binary symmetric channel (BSC). The LP decoder fails when it outputs a pseudo-codeword which is not a codeword. We propose an efficient algorithm termed the instanton search algorithm (ISA) which, given a random input, generates a set of flips called the BSC-instanton and prove that: (a) the LP decoder fails for any set of flips with support vector including an instanton; (b) for any input, the algorithm outputs an instanton in the number of steps upper-bounded by twice the number of flips in the input. We obtain the number of unique instantons of different sizes by running the ISA sufficient number of times. We then use the instanton statistics to predict the performance of the LP decoding over the BSC in the error floor region. We also propose an efficient semi-analytical method to predict the performance of LP decoding over a large range of transition probabilities of the BSC.
Hybrid EEG-fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control.
Khan, Muhammad Jawad; Hong, Keum-Shik
2017-01-01
In this paper, a hybrid electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain-computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG-fNIRS interface.
Hybrid EEG–fNIRS-Based Eight-Command Decoding for BCI: Application to Quadcopter Control
Khan, Muhammad Jawad; Hong, Keum-Shik
2017-01-01
In this paper, a hybrid electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) scheme to decode eight active brain commands from the frontal brain region for brain–computer interface is presented. A total of eight commands are decoded by fNIRS, as positioned on the prefrontal cortex, and by EEG, around the frontal, parietal, and visual cortices. Mental arithmetic, mental counting, mental rotation, and word formation tasks are decoded with fNIRS, in which the selected features for classification and command generation are the peak, minimum, and mean ΔHbO values within a 2-s moving window. In the case of EEG, two eyeblinks, three eyeblinks, and eye movement in the up/down and left/right directions are used for four-command generation. The features in this case are the number of peaks and the mean of the EEG signal during 1 s window. We tested the generated commands on a quadcopter in an open space. An average accuracy of 75.6% was achieved with fNIRS for four-command decoding and 86% with EEG for another four-command decoding. The testing results show the possibility of controlling a quadcopter online and in real-time using eight commands from the prefrontal and frontal cortices via the proposed hybrid EEG–fNIRS interface. PMID:28261084
Dissociable roles of internal feelings and face recognition ability in facial expression decoding.
Zhang, Lin; Song, Yiying; Liu, Ling; Liu, Jia
2016-05-15
The problem of emotion recognition has been tackled by researchers in both affective computing and cognitive neuroscience. While affective computing relies on analyzing visual features from facial expressions, it has been proposed that humans recognize emotions by internally simulating the emotional states conveyed by others' expressions, in addition to perceptual analysis of facial features. Here we investigated whether and how our internal feelings contributed to the ability to decode facial expressions. In two independent large samples of participants, we observed that individuals who generally experienced richer internal feelings exhibited a higher ability to decode facial expressions, and the contribution of internal feelings was independent of face recognition ability. Further, using voxel-based morphometry, we found that the gray matter volume (GMV) of bilateral superior temporal sulcus (STS) and the right inferior parietal lobule was associated with facial expression decoding through the mediating effect of internal feelings, while the GMV of bilateral STS, precuneus, and the right central opercular cortex contributed to facial expression decoding through the mediating effect of face recognition ability. In addition, the clusters in bilateral STS involved in the two components were neighboring yet separate. Our results may provide clues about the mechanism by which internal feelings, in addition to face recognition ability, serve as an important instrument for humans in facial expression decoding. Copyright © 2016 Elsevier Inc. All rights reserved.
Keibler, Evan; Arumugam, Manimozhiyan; Brent, Michael R
2007-03-01
Hidden Markov models (HMMs) and generalized HMMs been successfully applied to many problems, but the standard Viterbi algorithm for computing the most probable interpretation of an input sequence (known as decoding) requires memory proportional to the length of the sequence, which can be prohibitive. Existing approaches to reducing memory usage either sacrifice optimality or trade increased running time for reduced memory. We developed two novel decoding algorithms, Treeterbi and Parallel Treeterbi, and implemented them in the TWINSCAN/N-SCAN gene-prediction system. The worst case asymptotic space and time are the same as for standard Viterbi, but in practice, Treeterbi optimally decodes arbitrarily long sequences with generalized HMMs in bounded memory without increasing running time. Parallel Treeterbi uses the same ideas to split optimal decoding across processors, dividing latency to completion by approximately the number of available processors with constant average overhead per processor. Using these algorithms, we were able to optimally decode all human chromosomes with N-SCAN, which increased its accuracy relative to heuristic solutions. We also implemented Treeterbi for Pairagon, our pair HMM based cDNA-to-genome aligner. The TWINSCAN/N-SCAN/PAIRAGON open source software package is available from http://genes.cse.wustl.edu.
Sum of the Magnitude for Hard Decision Decoding Algorithm Based on Loop Update Detection
Directory of Open Access Journals (Sweden)
Jiahui Meng
2018-01-01
Full Text Available In order to improve the performance of non-binary low-density parity check codes (LDPC hard decision decoding algorithm and to reduce the complexity of decoding, a sum of the magnitude for hard decision decoding algorithm based on loop update detection is proposed. This will also ensure the reliability, stability and high transmission rate of 5G mobile communication. The algorithm is based on the hard decision decoding algorithm (HDA and uses the soft information from the channel to calculate the reliability, while the sum of the variable nodes’ (VN magnitude is excluded for computing the reliability of the parity checks. At the same time, the reliability information of the variable node is considered and the loop update detection algorithm is introduced. The bit corresponding to the error code word is flipped multiple times, before this is searched in the order of most likely error probability to finally find the correct code word. Simulation results show that the performance of one of the improved schemes is better than the weighted symbol flipping (WSF algorithm under different hexadecimal numbers by about 2.2 dB and 2.35 dB at the bit error rate (BER of 10−5 over an additive white Gaussian noise (AWGN channel, respectively. Furthermore, the average number of decoding iterations is significantly reduced.
Douik, Ahmed S.; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2015-01-01
This paper considers the multicast decoding delay reduction problem for generalized instantly decodable network coding (G-IDNC) over persistent erasure channels with feedback imperfections. The feedback scenario discussed is the most general situation in which the sender does not always receive acknowledgments from the receivers after each transmission and the feedback communications are subject to loss. The decoding delay increment expressions are derived and employed to express the decoding delay reduction problem as a maximum weight clique problem in the G-IDNC graph. This paper provides a theoretical analysis of the expected decoding delay increase at each time instant. Problem formulations in simpler channel and feedback models are shown to be special cases of the proposed generalized formulation. Since finding the optimal solution to the problem is known to be NP-hard, a suboptimal greedy algorithm is designed and compared with blind approaches proposed in the literature. Through extensive simulations, the proposed algorithm is shown to outperform the blind methods in all situations and to achieve significant improvement, particularly for high time-correlated channels.
Decoding complex flow-field patterns in visual working memory.
Christophel, Thomas B; Haynes, John-Dylan
2014-05-01
There has been a long history of research on visual working memory. Whereas early studies have focused on the role of lateral prefrontal cortex in the storage of sensory information, this has been challenged by research in humans that has directly assessed the encoding of perceptual contents, pointing towards a role of visual and parietal regions during storage. In a previous study we used pattern classification to investigate the storage of complex visual color patterns across delay periods. This revealed coding of such contents in early visual and parietal brain regions. Here we aim to investigate whether the involvement of visual and parietal cortex is also observable for other types of complex, visuo-spatial pattern stimuli. Specifically, we used a combination of fMRI and multivariate classification to investigate the retention of complex flow-field stimuli defined by the spatial patterning of motion trajectories of random dots. Subjects were trained to memorize the precise spatial layout of these stimuli and to retain this information during an extended delay. We used a multivariate decoding approach to identify brain regions where spatial patterns of activity encoded the memorized stimuli. Content-specific memory signals were observable in motion sensitive visual area MT+ and in posterior parietal cortex that might encode spatial information in a modality independent manner. Interestingly, we also found information about the memorized visual stimulus in somatosensory cortex, suggesting a potential crossmodal contribution to memory. Our findings thus indicate that working memory storage of visual percepts might be distributed across unimodal, multimodal and even crossmodal brain regions. Copyright © 2014 Elsevier Inc. All rights reserved.
Fast decoding techniques for extended single-and-double-error-correcting Reed Solomon codes
Costello, D. J., Jr.; Deng, H.; Lin, S.
1984-01-01
A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. For example, some 256K-bit dynamic random access memories are organized as 32K x 8 bit-bytes. Byte-oriented codes such as Reed Solomon (RS) codes provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special high speed decoding techniques for extended single and double error correcting RS codes. These techniques are designed to find the error locations and the error values directly from the syndrome without having to form the error locator polynomial and solve for its roots.
More than meets the eye: the role of self-identity in decoding complex emotional states.
Stevenson, Michael T; Soto, José A; Adams, Reginald B
2012-10-01
Folk wisdom asserts that "the eyes are the window to the soul," and empirical science corroborates a prominent role for the eyes in the communication of emotion. Herein we examine variation in the ability to "read" the eyes of others as a function of social group membership, employing a widely used emotional state decoding task: "Reading the Mind in Eyes." This task has documented impaired emotional state decoding across racial groups, with cross-race performance on par with that previously reported as a function of autism spectrum disorders. The present study extended this work by examining the moderating role of social identity in such impairments. For college students more highly identified with their university, cross-race performance differences were not found for judgments of "same-school" eyes but remained for "rival-school" eyes. These findings suggest that impaired emotional state decoding across groups may thus be more amenable to remediation than previously realized.
Decoding the content of visual short-term memory under distraction in occipital and parietal areas.
Bettencourt, Katherine C; Xu, Yaoda
2016-01-01
Recent studies have provided conflicting accounts regarding where in the human brain visual short-term memory (VSTM) content is stored, with strong univariate fMRI responses being reported in superior intraparietal sulcus (IPS), but robust multivariate decoding being reported in occipital cortex. Given the continuous influx of information in everyday vision, VSTM storage under distraction is often required. We found that neither distractor presence nor predictability during the memory delay affected behavioral performance. Similarly, superior IPS exhibited consistent decoding of VSTM content across all distractor manipulations and had multivariate responses that closely tracked behavioral VSTM performance. However, occipital decoding of VSTM content was substantially modulated by distractor presence and predictability. Furthermore, we found no effect of target-distractor similarity on VSTM behavioral performance, further challenging the role of sensory regions in VSTM storage. Overall, consistent with previous univariate findings, our results indicate that superior IPS, but not occipital cortex, has a central role in VSTM storage.
Analytical upper bound on optimum joint decoding capacity of Wyner GCMAC using hadamard inequality
Shakir, Muhammad
2011-11-01
This paper presents an original analytical expression for an upper bound on the optimum joint decoding capacity of Wyner circular Gaussian cellular multiple access channel (C-GCMAC) for uniformly distributed mobile terminals (MTs) across the cells. This upper bound is referred to as Hadamard upper bound (HUB) and is a novel application of the Hadamard inequality established by exploiting the Hadamard operation between the channel fading and channel path gain matrices. In this context, we employ an approximation approach based on the estimation of probability density function (PDF) of Hadamard product of two matrices. A closed-form expression has been derived to capture the effect of variable user density in adjacent cells on optimal joint decoding capacity. The results of this paper demonstrate that the analytical HUB based on the proposed approximation approach converges to the theoretical results for medium range of signal to noise ratios and shows a comparable tighter bound on optimum joint decoding capacity. © 2011 IEEE.
Jointly Decoded Raptor Codes: Analysis and Design for the BIAWGN Channel
Directory of Open Access Journals (Sweden)
Venkiah Auguste
2009-01-01
Full Text Available Abstract We are interested in the analysis and optimization of Raptor codes under a joint decoding framework, that is, when the precode and the fountain code exchange soft information iteratively. We develop an analytical asymptotic convergence analysis of the joint decoder, derive an optimization method for the design of efficient output degree distributions, and show that the new optimized distributions outperform the existing ones, both at long and moderate lengths. We also show that jointly decoded Raptor codes are robust to channel variation: they perform reasonably well over a wide range of channel capacities. This robustness property was already known for the erasure channel but not for the Gaussian channel. Finally, we discuss some finite length code design issues. Contrary to what is commonly believed, we show by simulations that using a relatively low rate for the precode , we can improve greatly the error floor performance of the Raptor code.
Blind Decoding of Multiple Description Codes over OFDM Systems via Sequential Monte Carlo
Directory of Open Access Journals (Sweden)
Guo Dong
2005-01-01
Full Text Available We consider the problem of transmitting a continuous source through an OFDM system. Multiple description scalar quantization (MDSQ is applied to the source signal, resulting in two correlated source descriptions. The two descriptions are then OFDM modulated and transmitted through two parallel frequency-selective fading channels. At the receiver, a blind turbo receiver is developed for joint OFDM demodulation and MDSQ decoding. Transformation of the extrinsic information of the two descriptions are exchanged between each other to improve system performance. A blind soft-input soft-output OFDM detector is developed, which is based on the techniques of importance sampling and resampling. Such a detector is capable of exchanging the so-called extrinsic information with the other component in the above turbo receiver, and successively improving the overall receiver performance. Finally, we also treat channel-coded systems, and a novel blind turbo receiver is developed for joint demodulation, channel decoding, and MDSQ source decoding.
On the reduced-complexity of LDPC decoders for ultra-high-speed optical transmission.
Djordjevic, Ivan B; Xu, Lei; Wang, Ting
2010-10-25
We propose two reduced-complexity (RC) LDPC decoders, which can be used in combination with large-girth LDPC codes to enable ultra-high-speed serial optical transmission. We show that optimally attenuated RC min-sum sum algorithm performs only 0.46 dB (at BER of 10(-9)) worse than conventional sum-product algorithm, while having lower storage memory requirements and much lower latency. We further study the use of RC LDPC decoding algorithms in multilevel coded modulation with coherent detection and show that with RC decoding algorithms we can achieve the net coding gain larger than 11 dB at BERs below 10(-9).
Fiber Bragg grating for spectral phase optical code-division multiple-access encoding and decoding
Fang, Xiaohui; Wang, Dong-Ning; Li, Shichen
2003-08-01
A new method for realizing spectral phase optical code-division multiple-access (OCDMA) coding based on step chirped fiber Bragg gratings (SCFBGs) is proposed and the corresponding encoder/decoder is presented. With this method, a mapping code is introduced for the m-sequence address code and the phase shift can be inserted into the subgratings of the SCFBG according to the mapping code. The transfer matrix method together with Fourier transform is used to investigate the characteristics of the encoder/decoder. The factors that influence the correlation property of the encoder/decoder, including index modulation and bandwidth of the subgrating, are identified. The system structure is simple and good correlation output can be obtained. The performance of the OCDMA system based on SCFBGs has been analyzed.
Institute of Scientific and Technical Information of China (English)
YUAN Dongfeng; WANG Chengxiang; YAO Qi; CAO Zhigang
2001-01-01
Based on "capacity rule", the perfor-mance of multilevel coding (MLC) schemes with dif-ferent set partitioning strategies and decoding meth-ods in AWGN and Rayleigh fading channels is investi-gated, in which BCH codes are chosen as componentcodes and 8ASK modulation is used. Numerical re-sults indicate that MLC scheme with UP strategy canobtain optimal performance in AWGN channels andBP is the best mapping strategy for Rayleigh fadingchannels. BP strategy is of good robustness in bothkinds of channels to realize an optimum MLC system.Multistage decoding (MSD) is a sub-optimal decodingmethod of MLC for both channels. For Ungerboeckpartitioning (UP) and mixed partitioning (MP) strat-egy, MSD is strongly recommended to use for MLCsystem, while for BP strategy, PDL is suggested to useas a simple decoding method compared with MSD.
Decoding the content of visual short-term memory under distraction in occipital and parietal areas
Bettencourt, Katherine C.; Xu, Yaoda
2015-01-01
Recent studies have provided conflicting accounts regarding where in the human brain visual short-term memory (VSTM) content is stored, with strong univariate fMRI responses reported in superior intraparietal sulcus (IPS) but robust multivariate decoding reported in occipital cortex. Given the continuous influx of information in everyday vision, VSTM storage under distraction is often required. We found that neither distractor presence nor predictability during the memory delay affected behavioral performance. Similarly, superior IPS exhibited consistent decoding of VSTM content across all distractor manipulations and had multivariate responses that closely tracked behavioral VSTM performance. However, occipital decoding of VSTM content was significantly modulated by distractor presence and predictability. Furthermore, we found no effect of target-distractor similarity on VSTM behavioral performance, further challenging the role of sensory regions in VSTM storage. Overall, consistent with previous univariate findings, these results show that superior IPS, not occipital cortex, plays a central role in VSTM storage. PMID:26595654
Liu, Hesheng; Agam, Yigal; Madsen, Joseph R.; Kreiman, Gabriel
2010-01-01
Summary The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms post-stimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feed-forward theories and provides strong constraints for computational models of human vision. PMID:19409272
International Nuclear Information System (INIS)
Jin, Dezhe Z
2008-01-01
Temporally complex stimuli are encoded into spatiotemporal spike sequences of neurons in many sensory areas. Here, we describe how downstream neurons with dendritic bistable plateau potentials can be connected to decode such spike sequences. Driven by feedforward inputs from the sensory neurons and controlled by feedforward inhibition and lateral excitation, the neurons transit between UP and DOWN states of the membrane potentials. The neurons spike only in the UP states. A decoding neuron spikes at the end of an input to signal the recognition of specific spike sequences. The transition dynamics is equivalent to that of a finite state automaton. A connection rule for the networks guarantees that any finite state automaton can be mapped into the transition dynamics, demonstrating the equivalence in computational power between the networks and finite state automata. The decoding mechanism is capable of recognizing an arbitrary number of spatiotemporal spike sequences, and is insensitive to the variations of the spike timings in the sequences
A Dual Coding Theoretical Model of Decoding in Reading: Subsuming the LaBerge and Samuels Model
Sadoski, Mark; McTigue, Erin M.; Paivio, Allan
2012-01-01
In this article we present a detailed Dual Coding Theory (DCT) model of decoding. The DCT model reinterprets and subsumes The LaBerge and Samuels (1974) model of the reading process which has served well to account for decoding behaviors and the processes that underlie them. However, the LaBerge and Samuels model has had little to say about…
Gallistel, Elizabeth; Fischer, Phyllis
This study evaluated the decoding skills acquired by low readers in an experimental project that taught low readers in regular class through the use of clinical procedures based on a synthetic phonic, multisensory approach. An evaluation instrument which permitted the tabulation of specific decoding skills was administered as a pretest and…
Lindner, Jennifer L.; Rosen, Lee A.
2006-01-01
This study examined differences in the ability to decode emotion through facial expression, prosody, and verbal content between 14 children with Asperger's Syndrome (AS) and 16 typically developing peers. The ability to decode emotion was measured by the Perception of Emotion Test (POET), which portrayed the emotions of happy, angry, sad, and…
Mirkovic, Bojana; Debener, Stefan; Jaeger, Manuela; De Vos, Maarten
2015-08-01
Objective. Recent studies have provided evidence that temporal envelope driven speech decoding from high-density electroencephalography (EEG) and magnetoencephalography recordings can identify the attended speech stream in a multi-speaker scenario. The present work replicated the previous high density EEG study and investigated the necessary technical requirements for practical attended speech decoding with EEG. Approach. Twelve normal hearing participants attended to one out of two simultaneously presented audiobook stories, while high density EEG was recorded. An offline iterative procedure eliminating those channels contributing the least to decoding provided insight into the necessary channel number and optimal cross-subject channel configuration. Aiming towards the future goal of near real-time classification with an individually trained decoder, the minimum duration of training data necessary for successful classification was determined by using a chronological cross-validation approach. Main results. Close replication of the previously reported results confirmed the method robustness. Decoder performance remained stable from 96 channels down to 25. Furthermore, for less than 15 min of training data, the subject-independent (pre-trained) decoder performed better than an individually trained decoder did. Significance. Our study complements previous research and provides information suggesting that efficient low-density EEG online decoding is within reach.
Deep learning with convolutional neural networks for EEG decoding and visualization.
Schirrmeister, Robin Tibor; Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio
2017-11-01
Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end-to-end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end-to-end EEG analysis, but a better understanding of how to design and train ConvNets for end-to-end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task-related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG-based brain mapping. Hum Brain Mapp 38:5391-5420, 2017. © 2017 Wiley Periodicals, Inc. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Elaine Anna Corbett
2014-05-01
Full Text Available Cervical spinal cord injury (SCI paralyzes muscles of the hand and arm, making it difficult to perform activities of daily living. Restoring the ability to reach can dramatically improve quality of life for people with cervical SCI. Any reaching system requires a user interface to decode parameters of an intended reach, such as trajectory and target. A challenge in developing such decoders is that often few physiological signals related to the intended reach remain under voluntary control, especially in patients with high cervical injuries. Furthermore, the decoding problem changes when the user is controlling the motion of their limb, as opposed to an external device. The purpose of this study was to investigate the benefits of combining disparate signal sources to control reach in people with a range of impairments, and to consider the effect of two feedback approaches. Subjects with cervical SCI performed robot-assisted reaching, controlling trajectories with either shoulder electromyograms (EMGs or EMGs combined with gaze. We then evaluated how reaching performance was influenced by task-related sensory feedback, testing the EMG-only decoder in two conditions. The first involved moving the arm with the robot, providing congruent sensory feedback through their remaining sense of proprioception. In the second, the subjects moved the robot without the arm attached, as in applications that control external devices. We found that the multimodal decoding algorithm worked well for all subjects, enabling them to perform straight, accurate reaches. The inclusion of gaze information, used to estimate target location, was especially important for the most impaired subjects. In the absence of gaze information, congruent sensory feedback improved performance. These results highlight the importance of proprioceptive feedback, and suggest that multi-modal decoders are likely to be most beneficial for highly impaired subjects and in tasks where such
Long-Term Asynchronous Decoding of Arm Motion Using Electrocorticographic Signals in Monkeys
Chao, Zenas C.; Nagasaka, Yasuo; Fujii, Naotaka
2009-01-01
Brain–machine interfaces (BMIs) employ the electrical activity generated by cortical neurons directly for controlling external devices and have been conceived as a means for restoring human cognitive or sensory-motor functions. The dominant approach in BMI research has been to decode motor variables based on single-unit activity (SUA). Unfortunately, this approach suffers from poor long-term stability and daily recalibration is normally required to maintain reliable performance. A possible alternative is BMIs based on electrocorticograms (ECoGs), which measure population activity and may provide more durable and stable recording. However, the level of long-term stability that ECoG-based decoding can offer remains unclear. Here we propose a novel ECoG-based decoding paradigm and show that we have successfully decoded hand positions and arm joint angles during an asynchronous food-reaching task in monkeys when explicit cues prompting the onset of movement were not required. Performance using our ECoG-based decoder was comparable to existing SUA-based systems while evincing far superior stability and durability. In addition, the same decoder could be used for months without any drift in accuracy or recalibration. These results were achieved by incorporating the spatio-spectro-temporal integration of activity across multiple cortical areas to compensate for the lower fidelity of ECoG signals. These results show the feasibility of high-performance, chronic and versatile ECoG-based neuroprosthetic devices for real-life applications. This new method provides a stable platform for investigating cortical correlates for understanding motor control, sensory perception, and high-level cognitive processes. PMID:20407639
Deep learning with convolutional neural networks for EEG decoding and visualization
Springenberg, Jost Tobias; Fiederer, Lukas Dominique Josef; Glasstetter, Martin; Eggensperger, Katharina; Tangermann, Michael; Hutter, Frank; Burgard, Wolfram; Ball, Tonio
2017-01-01
Abstract Deep learning with convolutional neural networks (deep ConvNets) has revolutionized computer vision through end‐to‐end learning, that is, learning from the raw data. There is increasing interest in using deep ConvNets for end‐to‐end EEG analysis, but a better understanding of how to design and train ConvNets for end‐to‐end EEG decoding and how to visualize the informative EEG features the ConvNets learn is still needed. Here, we studied deep ConvNets with a range of different architectures, designed for decoding imagined or executed tasks from raw EEG. Our results show that recent advances from the machine learning field, including batch normalization and exponential linear units, together with a cropped training strategy, boosted the deep ConvNets decoding performance, reaching at least as good performance as the widely used filter bank common spatial patterns (FBCSP) algorithm (mean decoding accuracies 82.1% FBCSP, 84.0% deep ConvNets). While FBCSP is designed to use spectral power modulations, the features used by ConvNets are not fixed a priori. Our novel methods for visualizing the learned features demonstrated that ConvNets indeed learned to use spectral power modulations in the alpha, beta, and high gamma frequencies, and proved useful for spatially mapping the learned features by revealing the topography of the causal contributions of features in different frequency bands to the decoding decision. Our study thus shows how to design and train ConvNets to decode task‐related information from the raw EEG without handcrafted features and highlights the potential of deep ConvNets combined with advanced visualization techniques for EEG‐based brain mapping. Hum Brain Mapp 38:5391–5420, 2017. © 2017 Wiley Periodicals, Inc. PMID:28782865
Decoding Speech With Integrated Hybrid Signals Recorded From the Human Ventral Motor Cortex
Directory of Open Access Journals (Sweden)
Kenji Ibayashi
2018-04-01
Full Text Available Restoration of speech communication for locked-in patients by means of brain computer interfaces (BCIs is currently an important area of active research. Among the neural signals obtained from intracranial recordings, single/multi-unit activity (SUA/MUA, local field potential (LFP, and electrocorticography (ECoG are good candidates for an input signal for BCIs. However, the question of which signal or which combination of the three signal modalities is best suited for decoding speech production remains unverified. In order to record SUA, LFP, and ECoG simultaneously from a highly localized area of human ventral sensorimotor cortex (vSMC, we fabricated an electrode the size of which was 7 by 13 mm containing sparsely arranged microneedle and conventional macro contacts. We determined which signal modality is the most capable of decoding speech production, and tested if the combination of these signals could improve the decoding accuracy of spoken phonemes. Feature vectors were constructed from spike frequency obtained from SUAs and event-related spectral perturbation derived from ECoG and LFP signals, then input to the decoder. The results showed that the decoding accuracy for five spoken vowels was highest when features from multiple signals were combined and optimized for each subject, and reached 59% when averaged across all six subjects. This result suggests that multi-scale signals convey complementary information for speech articulation. The current study demonstrated that simultaneous recording of multi-scale neuronal activities could raise decoding accuracy even though the recording area is limited to a small portion of cortex, which is advantageous for future implementation of speech-assisting BCIs.
A bidirectional brain-machine interface featuring a neuromorphic hardware decoder
Directory of Open Access Journals (Sweden)
Fabio Boi
2016-12-01
Full Text Available Bidirectional brain-machine interfaces (BMIs establish a two-way direct communication link4 between the brain and the external world. A decoder translates recorded neural activity into motor5 commands and an encoder delivers sensory information collected from the environment directly6 to the brain creating a closed-loop system. These two modules are typically integrated in bulky7 external devices. However, the clinical support of patients with severe motor and sensory deficits8 requires compact, low-power, and fully implantable systems that can decode neural signals to9 control external devices. As a first step toward this goal, we developed a modular bidirectional BMI10 setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented11 a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits.12 On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn13 to decode neural signals recorded from the brain into motor outputs controlling the movements14 of an external device. The modularity of the BMI allowed us to tune the individual components15 of the setup without modifying the whole system. In this paper we present the features of16 this modular BMI, and describe how we configured the network of spiking neuron circuits to17 implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm18 that connects bidirectionally the brain of an anesthetized rat with an external object. We show that19 the chip learned the decoding task correctly, allowing the interfaced brain to control the object’s20 trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is21 mature enough for the development of BMI modules that are sufficiently low-power and compact,22 while being highly computationally powerful and adaptive.
A Bidirectional Brain-Machine Interface Featuring a Neuromorphic Hardware Decoder.
Boi, Fabio; Moraitis, Timoleon; De Feo, Vito; Diotalevi, Francesco; Bartolozzi, Chiara; Indiveri, Giacomo; Vato, Alessandro
2016-01-01
Bidirectional brain-machine interfaces (BMIs) establish a two-way direct communication link between the brain and the external world. A decoder translates recorded neural activity into motor commands and an encoder delivers sensory information collected from the environment directly to the brain creating a closed-loop system. These two modules are typically integrated in bulky external devices. However, the clinical support of patients with severe motor and sensory deficits requires compact, low-power, and fully implantable systems that can decode neural signals to control external devices. As a first step toward this goal, we developed a modular bidirectional BMI setup that uses a compact neuromorphic processor as a decoder. On this chip we implemented a network of spiking neurons built using its ultra-low-power mixed-signal analog/digital circuits. On-chip on-line spike-timing-dependent plasticity synapse circuits enabled the network to learn to decode neural signals recorded from the brain into motor outputs controlling the movements of an external device. The modularity of the BMI allowed us to tune the individual components of the setup without modifying the whole system. In this paper, we present the features of this modular BMI and describe how we configured the network of spiking neuron circuits to implement the decoder and to coordinate it with the encoder in an experimental BMI paradigm that connects bidirectionally the brain of an anesthetized rat with an external object. We show that the chip learned the decoding task correctly, allowing the interfaced brain to control the object's trajectories robustly. Based on our demonstration, we propose that neuromorphic technology is mature enough for the development of BMI modules that are sufficiently low-power and compact, while being highly computationally powerful and adaptive.
Joint Source-Channel Decoding of Variable-Length Codes with Soft Information: A Survey
Directory of Open Access Journals (Sweden)
Pierre Siohan
2005-05-01
Full Text Available Multimedia transmission over time-varying wireless channels presents a number of challenges beyond existing capabilities conceived so far for third-generation networks. Efficient quality-of-service (QoS provisioning for multimedia on these channels may in particular require a loosening and a rethinking of the layer separation principle. In that context, joint source-channel decoding (JSCD strategies have gained attention as viable alternatives to separate decoding of source and channel codes. A statistical framework based on hidden Markov models (HMM capturing dependencies between the source and channel coding components sets the foundation for optimal design of techniques of joint decoding of source and channel codes. The problem has been largely addressed in the research community, by considering both fixed-length codes (FLC and variable-length source codes (VLC widely used in compression standards. Joint source-channel decoding of VLC raises specific difficulties due to the fact that the segmentation of the received bitstream into source symbols is random. This paper makes a survey of recent theoretical and practical advances in the area of JSCD with soft information of VLC-encoded sources. It first describes the main paths followed for designing efficient estimators for VLC-encoded sources, the key component of the JSCD iterative structure. It then presents the main issues involved in the application of the turbo principle to JSCD of VLC-encoded sources as well as the main approaches to source-controlled channel decoding. This survey terminates by performance illustrations with real image and video decoding systems.
Joint Source-Channel Decoding of Variable-Length Codes with Soft Information: A Survey
Guillemot, Christine; Siohan, Pierre
2005-12-01
Multimedia transmission over time-varying wireless channels presents a number of challenges beyond existing capabilities conceived so far for third-generation networks. Efficient quality-of-service (QoS) provisioning for multimedia on these channels may in particular require a loosening and a rethinking of the layer separation principle. In that context, joint source-channel decoding (JSCD) strategies have gained attention as viable alternatives to separate decoding of source and channel codes. A statistical framework based on hidden Markov models (HMM) capturing dependencies between the source and channel coding components sets the foundation for optimal design of techniques of joint decoding of source and channel codes. The problem has been largely addressed in the research community, by considering both fixed-length codes (FLC) and variable-length source codes (VLC) widely used in compression standards. Joint source-channel decoding of VLC raises specific difficulties due to the fact that the segmentation of the received bitstream into source symbols is random. This paper makes a survey of recent theoretical and practical advances in the area of JSCD with soft information of VLC-encoded sources. It first describes the main paths followed for designing efficient estimators for VLC-encoded sources, the key component of the JSCD iterative structure. It then presents the main issues involved in the application of the turbo principle to JSCD of VLC-encoded sources as well as the main approaches to source-controlled channel decoding. This survey terminates by performance illustrations with real image and video decoding systems.
Multi-level trellis coded modulation and multi-stage decoding
Costello, Daniel J., Jr.; Wu, Jiantian; Lin, Shu
1990-01-01
Several constructions for multi-level trellis codes are presented and many codes with better performance than previously known codes are found. These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets. New rotationally invariant multi-level trellis codes which can be combined with differential encoding to resolve phase ambiguity are presented.
Remote one-qubit information concentration and decoding of operator quantum error-correction codes
International Nuclear Information System (INIS)
Hsu Liyi
2007-01-01
We propose the general scheme of remote one-qubit information concentration. To achieve the task, the Bell-correlated mixed states are exploited. In addition, the nonremote one-qubit information concentration is equivalent to the decoding of the quantum error-correction code. Here we propose how to decode the stabilizer codes. In particular, the proposed scheme can be used for the operator quantum error-correction codes. The encoded state can be recreated on the errorless qubit, regardless how many bit-flip errors and phase-flip errors have occurred
An compression algorithm for medical images and a display with the decoding function
International Nuclear Information System (INIS)
Gotoh, Toshiyuki; Nakagawa, Yukihiro; Shiohara, Morito; Yoshida, Masumi
1990-01-01
This paper describes and efficient image compression method for medical images, a high-speed display with the decoding function. In our method, an input image is divided into blocks, and either of Discrete Cosine Transform coding (DCT) or Block Truncation Coding (BTC) is adaptively applied on each block to improve image quality. The display, we developed, receives the compressed data from the host computer and reconstruct images of good quality at high speed using four decoding microprocessors on which our algorithm is implemented in pipeline. By the experiments, our method and display were verified to be effective. (author)
Massey, J. L.
1976-01-01
The very low error probability obtained with long error-correcting codes results in a very small number of observed errors in simulation studies of practical size and renders the usual confidence interval techniques inapplicable to the observed error probability. A natural extension of the notion of a 'confidence interval' is made and applied to such determinations of error probability by simulation. An example is included to show the surprisingly great significance of as few as two decoding errors in a very large number of decoding trials.
Fast Erasure and Error decoding of Algebraic Geometry Codes up to the Feng-Rao Bound
DEFF Research Database (Denmark)
Jensen, Helge Elbrønd; Sakata, S.; Leonard, D.
1996-01-01
This paper gives an errata(that is erasure-and error-) decoding algorithm of one-point algebraic geometry codes up to the Feng-Rao designed minimum distance using Sakata's multidimensional generalization of the Berlekamp-massey algorithm and the votin procedure of Feng and Rao.......This paper gives an errata(that is erasure-and error-) decoding algorithm of one-point algebraic geometry codes up to the Feng-Rao designed minimum distance using Sakata's multidimensional generalization of the Berlekamp-massey algorithm and the votin procedure of Feng and Rao....
An HMM posterior decoder for sequence feature prediction that includes homology information
DEFF Research Database (Denmark)
Käll, Lukas; Krogh, Anders Stærmose; Sonnhammer, Erik L. L.
2005-01-01
Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines probabil......Motivation: When predicting sequence features like transmembrane topology, signal peptides, coil-coil structures, protein secondary structure or genes, extra support can be gained from homologs. Results: We present here a general hidden Markov model (HMM) decoding algorithm that combines......://phobius.cgb.ki.se/poly.html . An implementation of the algorithm is available on request from the authors....
Directory of Open Access Journals (Sweden)
Ahmed Abdulkadhim Hamad
2017-08-01
Full Text Available In this paper, different techniques are used to improve the turbo decoding of regular repeat accumulate (RA and irregular repeat accumulate (IRA codes. The adaptive scaling of a-posteriori information produced by Soft-output Viterbi decoder (SOVA is proposed. The encoded pilots are another scheme that applied for short length RA codes. This work also suggests a simple and a fast method to generate a random interleaver having a free 4 cycle Tanner graph. Progressive edge growth algorithm (PEG is also studied and simulated to create the Tanner graphs which have a great girth.
Scalable printed electronics: an organic decoder addressing ferroelectric non-volatile memory
Ng, Tse Nga; Schwartz, David E.; Lavery, Leah L.; Whiting, Gregory L.; Russo, Beverly; Krusor, Brent; Veres, Janos; Bröms, Per; Herlogsson, Lars; Alam, Naveed; Hagel, Olle; Nilsson, Jakob; Karlsson, Christer
2012-01-01
Scalable circuits of organic logic and memory are realized using all-additive printing processes. A 3-bit organic complementary decoder is fabricated and used to read and write non-volatile, rewritable ferroelectric memory. The decoder-memory array is patterned by inkjet and gravure printing on flexible plastics. Simulation models for the organic transistors are developed, enabling circuit designs tolerant of the variations in printed devices. We explain the key design rules in fabrication of complex printed circuits and elucidate the performance requirements of materials and devices for reliable organic digital logic. PMID:22900143
Implementation of IMDCT Block of an MP3 Decoder through Optimization on the DCT Matrix
Directory of Open Access Journals (Sweden)
M. Galabov
2004-12-01
Full Text Available The paper describes an attempt to create an efficient dedicatedMP3-decoder, according to the MPEG-1 Layer III standard. A new methodof Inverse Modified Discrete Cosine Transform by optimization on theDiscrete Cosine Transform (DCT matrix is proposed and an assemblerprogram for Digital Signal Processor is developed. In addition, aprogram to calculate DCT using Lee's algorithm for any matrix of thesize 2M is created. The experimental results have proven that thedecoder is able to stream and decode MP3 in real time.
Feature Selection Methods for Robust Decoding of Finger Movements in a Non-human Primate
Padmanaban, Subash; Baker, Justin; Greger, Bradley
2018-01-01
Objective: The performance of machine learning algorithms used for neural decoding of dexterous tasks may be impeded due to problems arising when dealing with high-dimensional data. The objective of feature selection algorithms is to choose a near-optimal subset of features from the original feature space to improve the performance of the decoding algorithm. The aim of our study was to compare the effects of four feature selection techniques, Wilcoxon signed-rank test, Relative Importance, Principal Component Analysis (PCA), and Mutual Information Maximization on SVM classification performance for a dexterous decoding task. Approach: A nonhuman primate (NHP) was trained to perform small coordinated movements—similar to typing. An array of microelectrodes was implanted in the hand area of the motor cortex of the NHP and used to record action potentials (AP) during finger movements. A Support Vector Machine (SVM) was used to classify which finger movement the NHP was making based upon AP firing rates. We used the SVM classification to examine the functional parameters of (i) robustness to simulated failure and (ii) longevity of classification. We also compared the effect of using isolated-neuron and multi-unit firing rates as the feature vector supplied to the SVM. Main results: The average decoding accuracy for multi-unit features and single-unit features using Mutual Information Maximization (MIM) across 47 sessions was 96.74 ± 3.5% and 97.65 ± 3.36% respectively. The reduction in decoding accuracy between using 100% of the features and 10% of features based on MIM was 45.56% (from 93.7 to 51.09%) and 4.75% (from 95.32 to 90.79%) for multi-unit and single-unit features respectively. MIM had best performance compared to other feature selection methods. Significance: These results suggest improved decoding performance can be achieved by using optimally selected features. The results based on clinically relevant performance metrics also suggest that the decoding
Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes
Mohammad Rakibul Islam; Dewan Siam Shafiullah; Muhammad Mostafa Amir Faisal; Imran Rahman
2011-01-01
Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the sam...
Convolutional Encoder and Viterbi Decoder Using SOPC For Variable Constraint Length
DEFF Research Database (Denmark)
Kulkarni, Anuradha; Dnyaneshwar, Mantri; Prasad, Neeli R.
2013-01-01
Convolution encoder and Viterbi decoder are the basic and important blocks in any Code Division Multiple Accesses (CDMA). They are widely used in communication system due to their error correcting capability But the performance degrades with variable constraint length. In this context to have...... detailed analysis, this paper deals with the implementation of convolution encoder and Viterbi decoder using system on programming chip (SOPC). It uses variable constraint length of 7, 8 and 9 bits for 1/2 and 1/3 code rates. By analyzing the Viterbi algorithm it is seen that our algorithm has a better...
The fast decoding of Reed-Solomon codes using high-radix fermat theoretic transforms
Liu, K. Y.; Reed, I. S.; Truong, T. K.
1976-01-01
Fourier-like transforms over GF(F sub n), where F sub n = 2(2n) + 1 is a Fermat prime, are applied in decoding Reed-Solomon codes. It is shown that such transforms can be computed using high-radix fast Fourier transform (FFT) algorithms requiring considerably fewer multiplications than the more usual radix 2 FFT algorithm. A special 256-symbol, 16-symbol-error-correcting, Reed-Solomon (RS) code for space communication-link applications can be encoded and decoded using this high-radix FFT algorithm over GF(F sub 3).
Modified Dynamic Decode-and-Forward Relaying Protocol for Type II Relay in LTE-Advanced and Beyond.
Nam, Sung Sik; Alouini, Mohamed-Slim; Choi, Seyeong
2016-01-01
In this paper, we propose a modified dynamic decode-and-forward (MoDDF) relaying protocol to meet the critical requirements for user equipment (UE) relays in next-generation cellular systems (e.g., LTE-Advanced and beyond). The proposed MoDDF realizes the fast jump-in relaying and the sequential decoding with an application of random codeset to encoding and re-encoding process at the source and the multiple UE relays, respectively. A subframe-by-subframe decoding based on the accumulated (or buffered) messages is employed to achieve energy, information, or mixed combining. Finally, possible early termination of decoding at the end user can lead to the higher spectral efficiency and more energy saving by reducing the frequency of redundant subframe transmission and decoding. These attractive features eliminate the need of directly exchanging control messages between multiple UE relays and the end user, which is an important prerequisite for the practical UE relay deployment.
"ON ALGEBRAIC DECODING OF Q-ARY REED-MULLER AND PRODUCT REED-SOLOMON CODES"
Energy Technology Data Exchange (ETDEWEB)
SANTHI, NANDAKISHORE [Los Alamos National Laboratory
2007-01-22
We consider a list decoding algorithm recently proposed by Pellikaan-Wu for q-ary Reed-Muller codes RM{sub q}({ell}, m, n) of length n {le} q{sup m} when {ell} {le} q. A simple and easily accessible correctness proof is given which shows that this algorithm achieves a relative error-correction radius of {tau} {le} (1-{radical}{ell}q{sup m-1}/n). This is an improvement over the proof using one-point Algebraic-Geometric decoding method given in. The described algorithm can be adapted to decode product Reed-Solomon codes. We then propose a new low complexity recursive aJgebraic decoding algorithm for product Reed-Solomon codes and Reed-Muller codes. This algorithm achieves a relative error correction radius of {tau} {le} {Pi}{sub i=1}{sup m} (1 - {radical}k{sub i}/q). This algorithm is then proved to outperform the Pellikaan-Wu algorithm in both complexity and error correction radius over a wide range of code rates.
Channel coding/decoding alternatives for compressed TV data on advanced planetary missions.
Rice, R. F.
1972-01-01
The compatibility of channel coding/decoding schemes with a specific TV compressor developed for advanced planetary missions is considered. Under certain conditions, it is shown that compressed data can be transmitted at approximately the same rate as uncompressed data without any loss in quality. Thus, the full gains of data compression can be achieved in real-time transmission.
Learning a common dictionary for subject-transfer decoding with resting calibration.
Morioka, Hiroshi; Kanemura, Atsunori; Hirayama, Jun-ichiro; Shikauchi, Manabu; Ogawa, Takeshi; Ikeda, Shigeyuki; Kawanabe, Motoaki; Ishii, Shin
2015-05-01
Brain signals measured over a series of experiments have inherent variability because of different physical and mental conditions among multiple subjects and sessions. Such variability complicates the analysis of data from multiple subjects and sessions in a consistent way, and degrades the performance of subject-transfer decoding in a brain-machine interface (BMI). To accommodate the variability in brain signals, we propose 1) a method for extracting spatial bases (or a dictionary) shared by multiple subjects, by employing a signal-processing technique of dictionary learning modified to compensate for variations between subjects and sessions, and 2) an approach to subject-transfer decoding that uses the resting-state activity of a previously unseen target subject as calibration data for compensating for variations, eliminating the need for a standard calibration based on task sessions. Applying our methodology to a dataset of electroencephalography (EEG) recordings during a selective visual-spatial attention task from multiple subjects and sessions, where the variability compensation was essential for reducing the redundancy of the dictionary, we found that the extracted common brain activities were reasonable in the light of neuroscience knowledge. The applicability to subject-transfer decoding was confirmed by improved performance over existing decoding methods. These results suggest that analyzing multisubject brain activities on common bases by the proposed method enables information sharing across subjects with low-burden resting calibration, and is effective for practical use of BMI in variable environments. Copyright © 2015 Elsevier Inc. All rights reserved.
Delay reduction in persistent erasure channels for generalized instantly decodable network coding
Sorour, Sameh
2013-06-01
In this paper, we consider the problem of minimizing the decoding delay of generalized instantly decodable network coding (G-IDNC) in persistent erasure channels (PECs). By persistent erasure channels, we mean erasure channels with memory, which are modeled as a Gilbert-Elliott two-state Markov model with good and bad channel states. In this scenario, the channel erasure dependence, represented by the transition probabilities of this channel model, is an important factor that could be exploited to reduce the decoding delay. We first formulate the G-IDNC minimum decoding delay problem in PECs as a maximum weight clique problem over the G-IDNC graph. Since finding the optimal solution of this formulation is NP-hard, we propose two heuristic algorithms to solve it and compare them using extensive simulations. Simulation results show that each of these heuristics outperforms the other in certain ranges of channel memory levels. They also show that the proposed heuristics significantly outperform both the optimal strict IDNC in the literature and the channel-unaware G-IDNC algorithms. © 2013 IEEE.
Performance analysis of a decoding algorithm for algebraic-geometry codes
DEFF Research Database (Denmark)
Høholdt, Tom; Jensen, Helge Elbrønd; Nielsen, Rasmus Refslund
1999-01-01
The fast decoding algorithm for one point algebraic-geometry codes of Sakata, Elbrond Jensen, and Hoholdt corrects all error patterns of weight less than half the Feng-Rao minimum distance. In this correspondence we analyze the performance of the algorithm for heavier error patterns. It turns out...
Video coding and decoding devices and methods preserving PPG relevant information
2015-01-01
The present invention relates to a video encoding device (10, 10', 10") and method for encoding video data and to a corresponding video decoding device (60, 60') and method. To preserve PPG relevant information after encoding without requiring a large amount of additional data for the video encoder
Video coding and decoding devices and methods preserving ppg relevant information
2013-01-01
The present invention relates to a video encoding device (10, 10', 10'') and method for encoding video data and to a corresponding video decoding device (60, 60') and method. To preserve PPG relevant information after encoding without requiring a large amount of additional data for the video encoder
The effect of tRNA levels on decoding times of mRNA codons.
Dana, Alexandra; Tuller, Tamir
2014-08-01
The possible effect of transfer ribonucleic acid (tRNA) concentrations on codons decoding time is a fundamental biomedical research question; however, due to a large number of variables affecting this process and the non-direct relation between them, a conclusive answer to this question has eluded so far researchers in the field. In this study, we perform a novel analysis of the ribosome profiling data of four organisms which enables ranking the decoding times of different codons while filtering translational phenomena such as experimental biases, extreme ribosomal pauses and ribosome traffic jams. Based on this filtering, we show for the first time that there is a significant correlation between tRNA concentrations and the codons estimated decoding time both in prokaryotes and in eukaryotes in natural conditions (-0.38 to -0.66, all P values decoding times are not correlated with aminoacyl-tRNA levels. The reported results support the conjecture that translation efficiency is directly influenced by the tRNA levels in the cell. Thus, they should help to understand the evolution of synonymous aspects of coding sequences via the adaptation of their codons to the tRNA pool. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam
2011-01-01
One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.
Toric Varieties and Codes, Error-correcting Codes, Quantum Codes, Secret Sharing and Decoding
DEFF Research Database (Denmark)
Hansen, Johan Peder
We present toric varieties and associated toric codes and their decoding. Toric codes are applied to construct Linear Secret Sharing Schemes (LSSS) with strong multiplication by the Massey construction. Asymmetric Quantum Codes are obtained from toric codes by the A.R. Calderbank P.W. Shor and A.......M. Steane construction of stabilizer codes (CSS) from linear codes containing their dual codes....
Performance analysis of linear codes under maximum-likelihood decoding: a tutorial
National Research Council Canada - National Science Library
Sason, Igal; Shamai, Shlomo
2006-01-01
..., upper and lower bounds on the error probability of linear codes under ML decoding are surveyed and applied to codes and ensembles of codes on graphs. For upper bounds, we discuss various bounds where focus is put on Gallager bounding techniques and their relation to a variety of other reported bounds. Within the class of lower bounds, we ad...
Cortical Decoding of Individual Finger and Wrist Kinematics for an Upper-Limb Neuroprosthesis
Aggarwal, Vikram; Tenore, Francesco; Acharya, Soumyadipta; Schieber, Marc H.; Thakor, Nitish V.
2010-01-01
Previous research has shown that neuronal activity can be used to continuously decode the kinematics of gross movements involving arm and hand trajectory. However, decoding the kinematics of fine motor movements, such as the manipulation of individual fingers, has not been demonstrated. In this study, single unit activities were recorded from task-related neurons in M1 of two trained rhesus monkey as they performed individuated movements of the fingers and wrist. The primates’ hand was placed in a manipulandum, and strain gauges at the tips of each finger were used to track the digit’s position. Both linear and non-linear filters were designed to simultaneously predict kinematics of each digit and the wrist, and their performance compared using mean squared error and correlation coefficients. All models had high decoding accuracy, but the feedforward ANN (R=0.76–0.86, MSE=0.04–0.05) and Kalman filter (R=0.68–0.86, MSE=0.04–0.07) performed better than a simple linear regression filter (0.58–0.81, 0.05–0.07). These results suggest that individual finger and wrist kinematics can be decoded with high accuracy, and be used to control a multi-fingered prosthetic hand in real-time. PMID:19964645
Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.
2016-10-01
Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.
Performance Analysis of CRC Codes for Systematic and Nonsystematic Polar Codes with List Decoding
Directory of Open Access Journals (Sweden)
Takumi Murata
2018-01-01
Full Text Available Successive cancellation list (SCL decoding of polar codes is an effective approach that can significantly outperform the original successive cancellation (SC decoding, provided that proper cyclic redundancy-check (CRC codes are employed at the stage of candidate selection. Previous studies on CRC-assisted polar codes mostly focus on improvement of the decoding algorithms as well as their implementation, and little attention has been paid to the CRC code structure itself. For the CRC-concatenated polar codes with CRC code as their outer code, the use of longer CRC code leads to reduction of information rate, whereas the use of shorter CRC code may reduce the error detection probability, thus degrading the frame error rate (FER performance. Therefore, CRC codes of proper length should be employed in order to optimize the FER performance for a given signal-to-noise ratio (SNR per information bit. In this paper, we investigate the effect of CRC codes on the FER performance of polar codes with list decoding in terms of the CRC code length as well as its generator polynomials. Both the original nonsystematic and systematic polar codes are considered, and we also demonstrate that different behaviors of CRC codes should be observed depending on whether the inner polar code is systematic or not.
Mellick, William; Sharp, Carla
2016-01-01
Several adult depression studies have investigated mental state decoding, the basis for theory of mind, using the Reading the Mind in the Eyes Test. Findings have been mixed, but a comprehensive study found a greater severity of depression to be associated with poorer mental state decoding. Importantly, there has yet to be a similar study of adolescent depression. Converging evidence suggests that atypical mental state decoding may have particularly profound effects for psychosocial functioning among depressed adolescent boys. Adolescent boys with major depressive disorder (MDD, n = 33) and sex-matched healthy controls (HCs, n = 84) completed structured clinical interviews, self-report measures of psychopathology and the Child Eyes Test (CET). The MDD group performed significantly better than HCs on the CET overall (p = 0.002), underscored by greater accuracy for negatively valenced items (p = 0.003). Group differences on items depicting positive (p = 0.129) and neutral mental states (p = 0.081) were nonsignificant. Enhanced mental state decoding among depressed adolescent boys may play a role in the maintenance of and vulnerability to adolescent depression. Findings and implications are discussed. Limitations of this study include a reliance on self-report data for HC boys, as well as a lack of 'pure' depression among the boys with MDD. © 2016 S. Karger AG, Basel.
Spelling Ability in College Students Predicted by Decoding, Print Exposure, and Vocabulary
Ocal, Turkan; Ehri, Linnea
2017-01-01
This study examines students' exposure to print, vocabulary and decoding as predictors of spelling skills. Participants were 42 college students (Mean age 22.5, SD = 7.87; 31 females and 11 males). Hierarchical regression analyses showed that most of the variance in spelling was explained by vocabulary knowledge. When vocabulary was entered first…
An area-efficient path memory structure for VLSI Implementation of high speed Viterbi decoders
DEFF Research Database (Denmark)
Paaske, Erik; Pedersen, Steen; Sparsø, Jens
1991-01-01
Path storage and selection methods for Viterbi decoders are investigated with special emphasis on VLSI implementations. Two well-known algorithms, the register exchange, algorithm, REA, and the trace back algorithm, TBA, are considered. The REA requires the smallest number of storage elements...
Balconi, Michela; Amenta, Simona; Ferrari, Chiara
2012-01-01
ASD subjects are described as showing particular difficulty in decoding emotional patterns. This paper explored linguistic and conceptual skills in response to emotional stimuli presented as emotional faces, scripts (pictures) and interactive situations (videos). Participants with autism, Asperger syndrome and control participants were shown…
Delay reduction in persistent erasure channels for generalized instantly decodable network coding
Sorour, Sameh; Aboutorab, Neda; Sadeghi, Parastoo; Karim, Mohammad Shahriar; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2013-01-01
In this paper, we consider the problem of minimizing the decoding delay of generalized instantly decodable network coding (G-IDNC) in persistent erasure channels (PECs). By persistent erasure channels, we mean erasure channels with memory, which are modeled as a Gilbert-Elliott two-state Markov model with good and bad channel states. In this scenario, the channel erasure dependence, represented by the transition probabilities of this channel model, is an important factor that could be exploited to reduce the decoding delay. We first formulate the G-IDNC minimum decoding delay problem in PECs as a maximum weight clique problem over the G-IDNC graph. Since finding the optimal solution of this formulation is NP-hard, we propose two heuristic algorithms to solve it and compare them using extensive simulations. Simulation results show that each of these heuristics outperforms the other in certain ranges of channel memory levels. They also show that the proposed heuristics significantly outperform both the optimal strict IDNC in the literature and the channel-unaware G-IDNC algorithms. © 2013 IEEE.
LDPC decoder with a limited-precision FPGA-based floating-point multiplication coprocessor
Moberly, Raymond; O'Sullivan, Michael; Waheed, Khurram
2007-09-01
Implementing the sum-product algorithm, in an FPGA with an embedded processor, invites us to consider a tradeoff between computational precision and computational speed. The algorithm, known outside of the signal processing community as Pearl's belief propagation, is used for iterative soft-decision decoding of LDPC codes. We determined the feasibility of a coprocessor that will perform product computations. Our FPGA-based coprocessor (design) performs computer algebra with significantly less precision than the standard (e.g. integer, floating-point) operations of general purpose processors. Using synthesis, targeting a 3,168 LUT Xilinx FPGA, we show that key components of a decoder are feasible and that the full single-precision decoder could be constructed using a larger part. Soft-decision decoding by the iterative belief propagation algorithm is impacted both positively and negatively by a reduction in the precision of the computation. Reducing precision reduces the coding gain, but the limited-precision computation can operate faster. A proposed solution offers custom logic to perform computations with less precision, yet uses the floating-point format to interface with the software. Simulation results show the achievable coding gain. Synthesis results help theorize the the full capacity and performance of an FPGA-based coprocessor.
2010-10-01
... 47 Telecommunication 1 2010-10-01 2010-10-01 false Closed caption decoder requirements for digital television receivers and converter boxes. 15.122 Section 15.122 Telecommunication FEDERAL COMMUNICATIONS... code spaces C2, C3, and G3 is optional. All unsupported graphic symbols in the G3 code space are to be...
Vale, Ana Paula
2011-01-01
This study examines the pronunciation of the first vowel in decoding disyllabic pseudowords derived from Portuguese words. Participants were 96 Portuguese monolinguals and 52 Portuguese-English bilinguals of equivalent Portuguese reading levels. The results indicate that sensitivity to vowel context emerges early, both in monolinguals and in…
Population decoding of motor cortical activity using a generalized linear model with hidden states.
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas; Paninski, Liam
2010-06-15
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (reducing the mean square error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. Copyright (c) 2010 Elsevier B.V. All rights reserved.
Aarnoutse, C.A.J.; Leeuwe, J.F.J. van; Voeten, M.J.M.; Oud, J.H.L.
2001-01-01
The goal of this study was (1) to investigate the development of decoding (efficiency), reading comprehension, vocabulary and spelling during the elementary school years and (2) to determine the differences between poor, average and good performers with regard to the development of these skills.
Decoding Pigeon Behavior Outcomes Using Functional Connections among Local Field Potentials.
Chen, Yan; Liu, Xinyu; Li, Shan; Wan, Hong
2018-01-01
Recent studies indicate that the local field potential (LFP) carries information about an animal's behavior, but issues regarding whether there are any relationships between the LFP functional networks and behavior tasks as well as whether it is possible to employ LFP network features to decode the behavioral outcome in a single trial remain unresolved. In this study, we developed a network-based method to decode the behavioral outcomes in pigeons by using the functional connectivity strength values among LFPs recorded from the nidopallium caudolaterale (NCL). In our method, the functional connectivity strengths were first computed based on the synchronization likelihood. Second, the strength values were unwrapped into row vectors and their dimensions were then reduced by principal component analysis. Finally, the behavioral outcomes in single trials were decoded using leave-one-out combined with the k -nearest neighbor method. The results showed that the LFP functional network based on the gamma-band was related to the goal-directed behavior of pigeons. Moreover, the accuracy of the network features (74 ± 8%) was significantly higher than that of the power features (61 ± 12%). The proposed method provides a powerful tool for decoding animal behavior outcomes using a neural functional network.
Decoding the industrial and digital city: visions of security in Holmes' and Sherlock’s London
Kustritz, A.; Kohnen, M.E.S.; Stein, L.E.; Busse, K.
2012-01-01
Both the original and BBC Sherlock Holmes rely on the science of deduction to solve crimes and dazzle audiences. Emerging in times of cultural transformation, both characters offer reassurance about safety in the city by decoding people and places using contemporary technologies. In industrial
Analytical upper bound on optimum joint decoding capacity of Wyner GCMAC using hadamard inequality
Shakir, Muhammad; Durrani, Tariq Salim; Alouini, Mohamed-Slim
2011-01-01
an approximation approach based on the estimation of probability density function (PDF) of Hadamard product of two matrices. A closed-form expression has been derived to capture the effect of variable user density in adjacent cells on optimal joint decoding
Generalised tally-based decoders for traitor tracing and group testing
Skoric, B.; de Groot, W.
2015-01-01
We propose a new type of score function for Tardos traitor tracing codes. It is related to the recently introduced tally-based score function, but it utilizes more of the information available to the decoder. It does this by keeping track of sequences of symbols in the distributed codewords instead
Combined fMRI- and eye movement-based decoding of bistable plaid motion perception.
Wilbertz, Gregor; Ketkar, Madhura; Guggenmos, Matthias; Sterzer, Philipp
2018-05-01
The phenomenon of bistable perception, in which perception alternates spontaneously despite constant sensory stimulation, has been particularly useful in probing the neural bases of conscious perception. The study of such bistability requires access to the observer's perceptual dynamics, which is usually achieved via active report. This report, however, constitutes a confounding factor in the study of conscious perception and can also be biased in the context of certain experimental manipulations. One approach to circumvent these problems is to track perceptual alternations using signals from the eyes or the brain instead of observers' reports. Here we aimed to optimize such decoding of perceptual alternations by combining eye and brain signals. Eye-tracking and functional magnetic resonance imaging (fMRI) was performed in twenty participants while they viewed a bistable visual plaid motion stimulus and reported perceptual alternations. Multivoxel pattern analysis (MVPA) for fMRI was combined with eye-tracking in a Support vector machine to decode participants' perceptual time courses from fMRI and eye-movement signals. While both measures individually already yielded high decoding accuracies (on average 86% and 88% correct, respectively) classification based on the two measures together further improved the accuracy (91% correct). These findings show that leveraging on both fMRI and eye movement data may pave the way for optimized no-report paradigms through improved decodability of bistable motion perception and hence for a better understanding of the neural correlates of consciousness. Copyright © 2018 Elsevier Inc. All rights reserved.
Gates, Louis
2017-12-11
The accompanying article introduces highly transparent grapheme-phoneme relationships embodied within a Periodic table of decoding cells, which arguably presents the quintessential transparent decoding elements. The study then folds these cells into one highly transparent but simply stated singularity generalization-this generalization unifies the decoding cells (97% transparency). Deeper, the periodic table and singularity generalization together highlight the connectivity of the periodic cells. Moreover, these interrelated cells, coupled with the singularity generalization, clarify teaching targets and enable efficient learning of the letter-sound code. This singularity generalization, in turn, serves as a model for creating unified but easily stated subordinate generalizations for any one of the transparent cells or groups of cells shown within the tables. The article then expands the periodic cells into two tables of teacher-ready sample word lists-one table includes sample words for the basic and phonogram vowel cells, and the other table embraces word samples for the transparent consonant cells. The paper concludes with suggestions for teaching the cellular transparency embedded within reoccurring isolated words and running text to promote decoding automaticity of the periodic cells.
The Effects of Musical Training on the Decoding Skills of German-Speaking Primary School Children
Rautenberg, Iris
2015-01-01
This paper outlines the results of a long-term study of 159 German-speaking primary school children. The correlations between musical skills (perception and differentiation of rhythmical and tonal/melodic patterns) and decoding skills, and the effects of musical training on word-level reading abilities were investigated. Cognitive skills and…
Effects of Training on Accuracy of Decoding Complex Nonverbal Behavior. Working Paper No. 267.
Atkinson, Michael L.; And Others
Two studies investigated the effects of training on how accurately observers (college students) decoded a complex nonverbal stimulus. In the first experiment, observers viewed silent videotapes of 16 third and fourth-grade school children who were listening to an easy or a difficult lesson. Half of the children were responding spontaneously, while…
Population Decoding of Motor Cortical Activity using a Generalized Linear Model with Hidden States
Lawhern, Vernon; Wu, Wei; Hatsopoulos, Nicholas G.; Paninski, Liam
2010-01-01
Generalized linear models (GLMs) have been developed for modeling and decoding population neuronal spiking activity in the motor cortex. These models provide reasonable characterizations between neural activity and motor behavior. However, they lack a description of movement-related terms which are not observed directly in these experiments, such as muscular activation, the subject's level of attention, and other internal or external states. Here we propose to include a multi-dimensional hidden state to address these states in a GLM framework where the spike count at each time is described as a function of the hand state (position, velocity, and acceleration), truncated spike history, and the hidden state. The model can be identified by an Expectation-Maximization algorithm. We tested this new method in two datasets where spikes were simultaneously recorded using a multi-electrode array in the primary motor cortex of two monkeys. It was found that this method significantly improves the model-fitting over the classical GLM, for hidden dimensions varying from 1 to 4. This method also provides more accurate decoding of hand state (lowering the Mean Square Error by up to 29% in some cases), while retaining real-time computational efficiency. These improvements on representation and decoding over the classical GLM model suggest that this new approach could contribute as a useful tool to motor cortical decoding and prosthetic applications. PMID:20359500
Outage performance of Decode-and-Forward partial selection in Nakagami-m fading channels
Benjillali, Mustapha; Alouini, Mohamed-Slim
2010-01-01
, selects the best relay to increase the chances of successful decoding and hence the possibility of cooperation when the direct link is also available. After deriving the exact distribution of the sum of two gamma variates with the same shape parameter
D-DSC: Decoding Delay-based Distributed Source Coding for Internet of Sensing Things.
Aktas, Metin; Kuscu, Murat; Dinc, Ergin; Akan, Ozgur B
2018-01-01
Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source Coding (D-DSC) to improve the energy efficiency of the classical DSC by employing the decoding delay concept which enables the use of the maximum correlated portion of sensor samples during the event estimation. In D-DSC, network is partitioned into clusters, where the clusterheads communicate their uncompressed samples carrying the side information, and the cluster members send their compressed samples. Sink performs joint decoding of the compressed and uncompressed samples and then reconstructs the event signal using the decoded sensor readings. Based on the observed degree of the correlation among sensor samples, the sink dynamically updates and broadcasts the varying compression rates back to the sensor nodes. Simulation results for the performance evaluation reveal that D-DSC can achieve reliable and energy-efficient event communication and estimation for practical signal detection/estimation applications having massive number of sensors towards the realization of Internet of Sensing Things (IoST).
Sanders, Gina
1985-01-01
Hearing and hearing-impaired children between ages 4.5 to 15.5 years in England and Belgium were invited to abstract the concept of emotion from photographs and line drawings of facial expressions and body postures. A further experiment isloated the element of context in the task of decoding expression of emotion, resulting in comparatively…
Directory of Open Access Journals (Sweden)
Hassibi Babak
2002-01-01
Full Text Available Multiple antenna systems are capable of providing high data rate transmissions over wireless channels. When the channels are dispersive, the signal at each receive antenna is a combination of both the current and past symbols sent from all transmit antennas corrupted by noise. The optimal receiver is a maximum-likelihood sequence detector and is often considered to be practically infeasible due to high computational complexity (exponential in number of antennas and channel memory. Therefore, in practice, one often settles for a less complex suboptimal receiver structure, typically with an equalizer meant to suppress both the intersymbol and interuser interference, followed by the decoder. We propose a sphere decoding for the sequence detection in multiple antenna communication systems over dispersive channels. The sphere decoding provides the maximum-likelihood estimate with computational complexity comparable to the standard space-time decision-feedback equalizing (DFE algorithms. The performance and complexity of the sphere decoding are compared with the DFE algorithm by means of simulations.
Hardware/Software Co-design Applied to Reed-Solomon Decoding for the DMB Standard
Dam, A.C.; Lammertink, M.G.J.; Rovers, K.C.; Slagman, J.; Wellink, A.M.; Rauwerda, G.K.; Smit, Gerardus Johannes Maria
2006-01-01
This paper addresses the implementation of Reed- Solomon decoding for battery-powered wireless devices. The scope of this paper is constrained by the Digital Media Broadcasting (DMB). The most critical element of the Reed-Solomon algorithm is implemented on two different reconfigurable hardware
A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control
Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.
2014-01-01
Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569
Restoring the Generalizability of SVM Based Decoding in High Dimensional Neuroimage Data
DEFF Research Database (Denmark)
Abrahamsen, Trine Julie; Hansen, Lars Kai
2011-01-01
Variance inflation is caused by a mismatch between linear projections of test and training data when projections are estimated on training sets smaller than the dimensionality of the feature space. We demonstrate that variance inflation can lead to an increased neuroimage decoding error rate...
Synthetic phonics and decodable instructional reading texts: How far do these support poor readers?
Price-Mohr, Ruth Maria; Price, Colin Bernard
2018-05-01
This paper presents data from a quasi-experimental trial with paired randomisation that emerged during the development of a reading scheme for children in England. This trial was conducted with a group of 12 children, aged 5-6, and considered to be falling behind their peers in reading ability and a matched control group. There were two intervention conditions (A: using mixed teaching methods and a high percentage of non-phonically decodable vocabulary; P: using mixed teaching methods and low percentage of non-decodable vocabulary); allocation to these was randomised. Children were assessed at pre- and post-test on standardised measures of receptive vocabulary, phoneme awareness, word reading, and comprehension. Two class teachers in the same school each selected 6 children, who they considered to be poor readers, to participate (n = 12). A control group (using synthetic phonics only and phonically decodable vocabulary) was selected from the same 2 classes based on pre-test scores for word reading (n = 16). Results from the study show positive benefits for poor readers from using both additional teaching methods (such as analytic phonics, sight word vocabulary, and oral vocabulary extension) in addition to synthetic phonics, and also non-decodable vocabulary in instructional reading text. Copyright © 2018 John Wiley & Sons, Ltd.
Czech Academy of Sciences Publication Activity Database
Košťál, Lubomír; Kobayashi, R.
2015-01-01
Roč. 136, Oct 2015 (2015), s. 3-10 ISSN 0303-2647 R&D Projects: GA ČR(CZ) GA15-08066S Institutional support: RVO:67985823 Keywords : neuronal coding * information transfer * optimal decoding Subject RIV: BD - Theory of Information Impact factor: 1.495, year: 2015
A best-first tree-searching approach for ML decoding in MIMO system
Shen, Chung-An; Eltawil, Ahmed M.; Mondal, Sudip; Salama, Khaled N.
2012-01-01
In MIMO communication systems maximum-likelihood (ML) decoding can be formulated as a tree-searching problem. This paper presents a tree-searching approach that combines the features of classical depth-first and breadth-first approaches to achieve
High-Speed Soft-Decision Decoding of Two Reed-Muller Codes
Lin, Shu; Uehara, Gregory T.
1996-01-01
In his research, we have proposed the (64, 40, 8) subcode of the third-order Reed-Muller (RM) code to NASA for high-speed satellite communications. This RM subcode can be used either alone or as an inner code of a concatenated coding system with the NASA standard (255, 233, 33) Reed-Solomon (RS) code as the outer code to achieve high performance (or low bit-error rate) with reduced decoding complexity. It can also be used as a component code in a multilevel bandwidth efficient coded modulation system to achieve reliable bandwidth efficient data transmission. This report will summarize the key progress we have made toward achieving our eventual goal of implementing a decoder system based upon this code. In the first phase of study, we investigated the complexities of various sectionalized trellis diagrams for the proposed (64, 40, 8) RNI subcode. We found a specific 8-trellis diagram for this code which requires the least decoding complexity with a high possibility of achieving a decoding speed of 600 M bits per second (Mbps). The combination of a large number of states and a hi ch data rate will be made possible due to the utilization of a high degree of parallelism throughout the architecture. This trellis diagram will be presented and briefly described. In the second phase of study which was carried out through the past year, we investigated circuit architectures to determine the feasibility of VLSI implementation of a high-speed Viterbi decoder based on this 8-section trellis diagram. We began to examine specific design and implementation approaches to implement a fully custom integrated circuit (IC) which will be a key building block for a decoder system implementation. The key results will be presented in this report. This report will be divided into three primary sections. First, we will briefly describe the system block diagram in which the proposed decoder is assumed to be operating and present some of the key architectural approaches being used to
Coder and decoder of fractal signals of comb-type structure
Directory of Open Access Journals (Sweden)
Politanskyi R. L.
2014-08-01
Full Text Available The article presents a coder and decoder of fractal signals of comb-type structure (FSCS based on microcontrollers (MC. The coder and decoder consist of identical control modules, while their managed modules have different schematic constructions. The control module performs forming or recognition of signals, and also carries out the function of information exchange with a computer. The basic element of the control module is a PIC18F2550 microcontroller from MicroChip. The coder of the system forms fractal signals of a given order according to the information bits coming from the computer. Samples of the calculated values of the amplitudes of elementary rectangular pulses that constitute the structure of fractal pulses are stored in the memory of the microcontroller as a table. Minimum bit capacity of the DAC necessary for the generation of FSCS of fourth order is four bits. The operation algorithm, "wired" into the controller of the program, provides for encoding of the transmitted information by two-bit symbols. Recognition of the start of transmission of each byte in communication channel is performed by the transmission of the timing signal. In a decoder the microcontroller carries out reception and decoding of the received fractal signals which are then transmitted to the computer. The developed algorithm of the program for the microcontroller of the decoder is carried out by determination of order of fractal impulse after the value of sum of amplitudes of elementary impulses, constituents fractal signal. The programs for coder and decoder are written in "C". In the most critical places of the program influencing on the fast-acting of chart “assembler” insertions are done. The blocks of the coder and decoder were connected with a coaxial 10 meters long cable with an impendance of 75 Ohm. The signals generated by the developed coder of FSCS, were studied using a digital oscillograph. On the basis of the obtained spectrums, it is possible
Population coding and decoding in a neural field: a computational study.
Wu, Si; Amari, Shun-Ichi; Nakahara, Hiroyuki
2002-05-01
This study uses a neural field model to investigate computational aspects of population coding and decoding when the stimulus is a single variable. A general prototype model for the encoding process is proposed, in which neural responses are correlated, with strength specified by a gaussian function of their difference in preferred stimuli. Based on the model, we study the effect of correlation on the Fisher information, compare the performances of three decoding methods that differ in the amount of encoding information being used, and investigate the implementation of the three methods by using a recurrent network. This study not only rediscovers main results in existing literatures in a unified way, but also reveals important new features, especially when the neural correlation is strong. As the neural correlation of firing becomes larger, the Fisher information decreases drastically. We confirm that as the width of correlation increases, the Fisher information saturates and no longer increases in proportion to the number of neurons. However, we prove that as the width increases further--wider than (sqrt)2 times the effective width of the turning function--the Fisher information increases again, and it increases without limit in proportion to the number of neurons. Furthermore, we clarify the asymptotic efficiency of the maximum likelihood inference (MLI) type of decoding methods for correlated neural signals. It shows that when the correlation covers a nonlocal range of population (excepting the uniform correlation and when the noise is extremely small), the MLI type of method, whose decoding error satisfies the Cauchy-type distribution, is not asymptotically efficient. This implies that the variance is no longer adequate to measure decoding accuracy.
Directory of Open Access Journals (Sweden)
Elaine Astrand
Full Text Available Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fields (FEF: the spatial position of a visual cue, and the instructed orientation of the animal's attention. While the first variable is exogenously driven by the environment, the second variable corresponds to the interpretation of the instruction conveyed by the cue; it is endogenously driven and corresponds to the output of internal cognitive operations performed on the visual attributes of the cue. These two variables were decoded using either a regularized optimal linear estimator in its explicit formulation, an optimal linear artificial neural network estimator, a non-linear artificial neural network estimator, a non-linear naïve Bayesian estimator, a non-linear Reservoir recurrent network classifier or a non-linear Support Vector Machine classifier. Our results suggest that endogenous information such as the orientation of attention can be decoded from the FEF with the same accuracy as exogenous visual information. All classifiers did not behave equally in the face of population size and heterogeneity, the available training and testing trials, the subject's behavior and the temporal structure of the variable of interest. In most situations, the regularized optimal linear estimator and the non-linear Support Vector Machine classifiers outperformed the other tested decoders.
Directory of Open Access Journals (Sweden)
Alex Brandmeyer
Full Text Available Brain-computer interfaces (BCIs are systems that use real-time analysis of neuroimaging data to determine the mental state of their user for purposes such as providing neurofeedback. Here, we investigate the feasibility of a BCI based on speech perception. Multivariate pattern classification methods were applied to single-trial EEG data collected during speech perception by native and non-native speakers. Two principal questions were asked: 1 Can differences in the perceived categories of pairs of phonemes be decoded at the single-trial level? 2 Can these same categorical differences be decoded across participants, within or between native-language groups? Results indicated that classification performance progressively increased with respect to the categorical status (within, boundary or across of the stimulus contrast, and was also influenced by the native language of individual participants. Classifier performance showed strong relationships with traditional event-related potential measures and behavioral responses. The results of the cross-participant analysis indicated an overall increase in average classifier performance when trained on data from all participants (native and non-native. A second cross-participant classifier trained only on data from native speakers led to an overall improvement in performance for native speakers, but a reduction in performance for non-native speakers. We also found that the native language of a given participant could be decoded on the basis of EEG data with accuracy above 80%. These results indicate that electrophysiological responses underlying speech perception can be decoded at the single-trial level, and that decoding performance systematically reflects graded changes in the responses related to the phonological status of the stimuli. This approach could be used in extensions of the BCI paradigm to support perceptual learning during second language acquisition.
Distinct neural patterns enable grasp types decoding in monkey dorsal premotor cortex
Hao, Yaoyao; Zhang, Qiaosheng; Controzzi, Marco; Cipriani, Christian; Li, Yue; Li, Juncheng; Zhang, Shaomin; Wang, Yiwen; Chen, Weidong; Chiara Carrozza, Maria; Zheng, Xiaoxiang
2014-12-01
Objective. Recent studies have shown that dorsal premotor cortex (PMd), a cortical area in the dorsomedial grasp pathway, is involved in grasp movements. However, the neural ensemble firing property of PMd during grasp movements and the extent to which it can be used for grasp decoding are still unclear. Approach. To address these issues, we used multielectrode arrays to record both spike and local field potential (LFP) signals in PMd in macaque monkeys performing reaching and grasping of one of four differently shaped objects. Main results. Single and population neuronal activity showed distinct patterns during execution of different grip types. Cluster analysis of neural ensemble signals indicated that the grasp related patterns emerged soon (200-300 ms) after the go cue signal, and faded away during the hold period. The timing and duration of the patterns varied depending on the behaviors of individual monkey. Application of support vector machine model to stable activity patterns revealed classification accuracies of 94% and 89% for each of the two monkeys, indicating a robust, decodable grasp pattern encoded in the PMd. Grasp decoding using LFPs, especially the high-frequency bands, also produced high decoding accuracies. Significance. This study is the first to specify the neuronal population encoding of grasp during the time course of grasp. We demonstrate high grasp decoding performance in PMd. These findings, combined with previous evidence for reach related modulation studies, suggest that PMd may play an important role in generation and maintenance of grasp action and may be a suitable locus for brain-machine interface applications.
Decoding facial expressions based on face-selective and motion-sensitive areas.
Liang, Yin; Liu, Baolin; Xu, Junhai; Zhang, Gaoyan; Li, Xianglin; Wang, Peiyuan; Wang, Bin
2017-06-01
Humans can easily recognize others' facial expressions. Among the brain substrates that enable this ability, considerable attention has been paid to face-selective areas; in contrast, whether motion-sensitive areas, which clearly exhibit sensitivity to facial movements, are involved in facial expression recognition remained unclear. The present functional magnetic resonance imaging (fMRI) study used multi-voxel pattern analysis (MVPA) to explore facial expression decoding in both face-selective and motion-sensitive areas. In a block design experiment, participants viewed facial expressions of six basic emotions (anger, disgust, fear, joy, sadness, and surprise) in images, videos, and eyes-obscured videos. Due to the use of multiple stimulus types, the impacts of facial motion and eye-related information on facial expression decoding were also examined. It was found that motion-sensitive areas showed significant responses to emotional expressions and that dynamic expressions could be successfully decoded in both face-selective and motion-sensitive areas. Compared with static stimuli, dynamic expressions elicited consistently higher neural responses and decoding performance in all regions. A significant decrease in both activation and decoding accuracy due to the absence of eye-related information was also observed. Overall, the findings showed that emotional expressions are represented in motion-sensitive areas in addition to conventional face-selective areas, suggesting that motion-sensitive regions may also effectively contribute to facial expression recognition. The results also suggested that facial motion and eye-related information played important roles by carrying considerable expression information that could facilitate facial expression recognition. Hum Brain Mapp 38:3113-3125, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
International Nuclear Information System (INIS)
Proklov, V V; Byshevski-Konopko, O A; Filatov, A L; Lugovskoi, A V; Pisarevsky, Yu V
2016-01-01
A prototype of the acousto-optic (AO) decoder of optical signals is created on the base of the multiband AO filter. The joint work of the decoder with the developed previously AO coder has been verified experimentally. The main qualitative and quantitate characteristics of the spectral coding and decoding by Walsh sequences of the industrial LED radiation in the near infrared range are investigated. It is shown, that in the proposed data transmission system realization Signal-to-Interference Ratio (SIR) is not less than 13 dB. (paper)
List Decoding of Matrix-Product Codes from nested codes: an application to Quasi-Cyclic codes
DEFF Research Database (Denmark)
Hernando, Fernando; Høholdt, Tom; Ruano, Diego
2012-01-01
A list decoding algorithm for matrix-product codes is provided when $C_1,..., C_s$ are nested linear codes and $A$ is a non-singular by columns matrix. We estimate the probability of getting more than one codeword as output when the constituent codes are Reed-Solomon codes. We extend this list...... decoding algorithm for matrix-product codes with polynomial units, which are quasi-cyclic codes. Furthermore, it allows us to consider unique decoding for matrix-product codes with polynomial units....
International Nuclear Information System (INIS)
Hasegawa, Takeo; Hashiba, Hiroshi; Akagi, Kiyoshi; Kobayashi, Akitoshi; Matsuda, Magoichi
1979-01-01
Research has been done on optically reconstructed imaging employing the Multiple Pinhole Coded Aperture (hereafter abbreviated as MPCA) in radioisotope tomographic imaging. However, problems remain in the optically reconstructed image method. Therefore, we employed a minicomputer (hereafter abbreviated as CPU) and developed the software for decoding and managing the radioisotope tomographic image. Combining the MPCA and the CPU system, we were able to decode and manage the radioisotope tomographic image. 1) In comparison to the optically decoded MPCA image, various input commands are possibly in the CPU method according to the dialogue between the CPU and the on line typewriter. In addition to this, decoded tomographic images of unrestricted depth are readily attainable. 2) In the CPU method noise elimination and other aspects of image management can be easily performed. (author)
Lapotre, Vianney; Gogniat, Guy; Baghdadi, Amer; Diguet, Jean-Philippe
2017-12-01
The multiplication of connected devices goes along with a large variety of applications and traffic types needing diverse requirements. Accompanying this connectivity evolution, the last years have seen considerable evolutions of wireless communication standards in the domain of mobile telephone networks, local/wide wireless area networks, and Digital Video Broadcasting (DVB). In this context, intensive research has been conducted to provide flexible turbo decoder targeting high throughput, multi-mode, multi-standard, and power consumption efficiency. However, flexible turbo decoder implementations have not often considered dynamic reconfiguration issues in this context that requires high speed configuration switching. Starting from this assessment, this paper proposes the first solution that allows frame-by-frame run-time configuration management of a multi-processor turbo decoder without compromising the decoding performances.
Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang
2014-01-01
Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.