Linearity optimization of edge filter demodulators in FBGs
Li, Dong-Sheng; Sui, Qing-Mei; Cao, Yu-Qiang
2008-05-01
A kind of electric circuit is improved to optimize the linearity of edge filter demodulators in FBGs. By using a logarithm amplifier and an extraction operation, the linear range of optimized edge filter demodulators has been broadened effectively, and the requirement of optical filter’s linear range has been reduced. Theoretical analyses and the simulation results indicated that the linear range of optimized edge filter demodulator’s covers the whole transition region of the edge filter, while a strict linearity of the optical filter is not necessary.
Non-linear DSGE Models and The Optimized Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper improves the accuracy and speed of particle filtering for non-linear DSGE models with potentially non-normal shocks. This is done by introducing a new proposal distribution which i) incorporates information from new observables and ii) has a small optimization step that minimizes...... the distance to the optimal proposal distribution. A particle filter with this proposal distribution is shown to deliver a high level of accuracy even with relatively few particles, and this filter is therefore much more efficient than the standard particle filter....
Non-linear and signal energy optimal asymptotic filter design
Directory of Open Access Journals (Sweden)
Josef Hrusak
2003-10-01
Full Text Available The paper studies some connections between the main results of the well known Wiener-Kalman-Bucy stochastic approach to filtering problems based mainly on the linear stochastic estimation theory and emphasizing the optimality aspects of the achieved results and the classical deterministic frequency domain linear filters such as Chebyshev, Butterworth, Bessel, etc. A new non-stochastic but not necessarily deterministic (possibly non-linear alternative approach called asymptotic filtering based mainly on the concepts of signal power, signal energy and a system equivalence relation plays an important role in the presentation. Filtering error invariance and convergence aspects are emphasized in the approach. It is shown that introducing the signal power as the quantitative measure of energy dissipation makes it possible to achieve reasonable results from the optimality point of view as well. The property of structural energy dissipativeness is one of the most important and fundamental features of resulting filters. Therefore, it is natural to call them asymptotic filters. The notion of the asymptotic filter is carried in the paper as a proper tool in order to unify stochastic and non-stochastic, linear and nonlinear approaches to signal filtering.
An Optimal Transport Formulation of the Linear Feedback Particle Filter
Taghvaei, Amirhossein; Mehta, Prashant G.
2015-01-01
Feedback particle filter (FPF) is an algorithm to numerically approximate the solution of the nonlinear filtering problem in continuous time. The algorithm implements a feedback control law for a system of particles such that the empirical distribution of particles approximates the posterior distribution. However, it has been noted in the literature that the feedback control law is not unique. To find a unique control law, the filtering task is formulated here as an optimal transportation pro...
Noise Reduction with Optimal Variable Span Linear Filters
DEFF Research Database (Denmark)
Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll
2016-01-01
of eigenvectors stemming from a joint diagonalization of the covariance matrices of the signal of interest and the noise. The resulting filters are flexible in that it is possible to trade off distortion of the desired signal for improved noise reduction. This tradeoff is controlled by the number of eigenvectors...
Energy Technology Data Exchange (ETDEWEB)
Sun, Winston Y. [Univ. of California, Berkeley, CA (United States)
1993-04-01
This thesis solves the problem of finding the optimal linear noise-reduction filter for linear tomographic image reconstruction. The optimization is data dependent and results in minimizing the mean-square error of the reconstructed image. The error is defined as the difference between the result and the best possible reconstruction. Applications for the optimal filter include reconstructions of positron emission tomographic (PET), X-ray computed tomographic, single-photon emission tomographic, and nuclear magnetic resonance imaging. Using high resolution PET as an example, the optimal filter is derived and presented for the convolution backprojection, Moore-Penrose pseudoinverse, and the natural-pixel basis set reconstruction methods. Simulations and experimental results are presented for the convolution backprojection method.
Big Bang–Big Crunch Optimization Algorithm for Linear Phase Fir Digital Filter Design
Directory of Open Access Journals (Sweden)
Ms. Rashmi Singh Dr. H. K. Verma
2012-02-01
Full Text Available The Big Bang–Big Crunch (BB–BC optimization algorithm is a new optimization method that relies on the Big Bang and Big Crunch theory, one of the theories of the evolution of the universe. In this paper, a Big Bang–Big Crunch algorithm has been used here for the design of linear phase finite impulse response (FIR filters. Here the experimented fitness function based on the mean squared error between the actual and the ideal filter response. This paper presents the plot of magnitude response of FIR filters and error graph. The BB-BC seems to be promising tool for FIR filter design especially in a dynamic environment where filter coefficients have to be adapted and fast convergence is of importance.
Linear variable filter optimization for emergency response chemical detection and discrimination
Shen, Sylvia S.; Lewis, Paul E.
2010-08-01
Linear variable filter design and fabrication for LWIR is now commercially available for use in the development of remote sensing systems. The linear variable filter is attached directly to the cold shield of the focal plane array. The resulting compact spectrometer assemblies are completely contained in the Dewar system. This approach eliminates many of the wavelength calibration problems associated with current prism and grating systems and also facilitates the cost effective design and fabrication of aerial sensing systems for specific applications. This paper describes a study that was conducted with the following three objectives: 1) Determine if a multi-channel linear-variable-filter-based line scanner system can be used to discriminate a set of chemical vapors that represent a high probability of occurrence during a typical emergency response chemical incident; 2) Determine which multi-channel linear variable filter design is optimal; and 3) Determine the acceptable instrument noise equivalent spectral radiance for this application. A companion paper describes a separate study that was conducted to determine the concentration levels at which detection and discrimination can be achieved for the various chemicals based on the optimal filter design under various degrees of imperfect atmospheric correction.
Optimal Linear Filters for Pulse Height Measurements in the Presence of Noise
Energy Technology Data Exchange (ETDEWEB)
Nygaard, K.
1966-07-15
For measurements of nuclear pulse height spectra a linear filter is used between the pulse amplifier and the pulse height recorder so as to improve the signal/noise ratio. The problem of finding the optimal filter is investigated with emphasis on technical realizability. The maximum available signal/noise ratio is theoretically calculated on the basis of all the information which can be found in the output of the pulse amplifier, and on an assumed a priori knowledge of the pulse time of arrival. It is then shown that the maximum available signal/noise ratio can be obtained with practical measurements without any a priori knowledge of pulse time of arrival, and a general description of the optimal linear filter is given. The solution is unique, technically realizable, and based solely on data (noise power spectrum and pulse shape) which can be measured at the output terminals of the pulse amplifier used.
Anderson, Brian D O
2005-01-01
This graduate-level text augments and extends beyond undergraduate studies of signal processing, particularly in regard to communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to students in such diverse areas as statistics, economics, bioengineering, and operations research.Topics include filtering, linear systems, and estimation; the discrete-time Kalman filter; time-invariant filters; properties of Kalman filters; computational aspects; and smoothing of discrete-time signals. Additional subjects e
Institute of Scientific and Technical Information of China (English)
Hong-Ling Ye; Wei-Wei Wang; Ning Chen; Yun-Kang Sui
2016-01-01
In this paper, a model of topology optimization with linear buckling constraints is established based on an independent and continuous mapping method to minimize the plate/shell structure weight. A composite exponential function (CEF) is selected as filtering functions for element weight, the element stiffness matrix and the element geomet-ric stiffness matrix, which recognize the design variables, and to implement the changing process of design variables from“discrete”to“continuous”and back to“discrete”. The buck-ling constraints are approximated as explicit formulations based on the Taylor expansion and the filtering function. The optimization model is transformed to dual programming and solved by the dual sequence quadratic programming algo-rithm. Finally, three numerical examples with power function and CEF as filter function are analyzed and discussed to demonstrate the feasibility and efficiency of the proposed method.
Directory of Open Access Journals (Sweden)
Jian Ding
2013-11-01
Full Text Available This paper is concerned with the linear unbiased minimum variance estimation problem for discrete-time stochastic linear control systems with one-step random delay and inconsecutive packet dropout. A new model is developed to describe the phenomena of the one-step delay and inconsecutive packet dropout by employing a Bernoulli distributed stochastic variable. Based on the model, a recursive linear unbiased optimal filter in the linear minimum variance sense is designed by the method of completing the square. The solution to the linear filter is given by three equations including a Riccati equation, a Lyapunov equation and a simple difference equation. A sufficient condition for the existence of the steady-state filter is given. A simulation shows the effectiveness of the proposed algorithm.
On Optimal Linear Filtering of Speech for Near-End Listening Enhancement
DEFF Research Database (Denmark)
Taal, Cees H.; Jensen, Jesper; Leijon, Arne
2013-01-01
In this letter the focus is on linear filtering of speech before degradation due to additive background noise. The goal is to design the filter such that the speech intelligibility index (SII) is maximized when the speech is played back in a known noisy environment. Moreover, a power constraint...... suboptimal. In this work we propose a nonlinear approximation of the SII which is accurate for all SNRs. Experiments show large intelligibility improvements with the proposed method over the unprocessed noisy speech and better performance than one state-of-the art method....
Gozani, S N; Miller, J P
1994-04-01
We describe advanced protocols for the discrimination and classification of neuronal spike waveforms within multichannel electrophysiological recordings. The programs are capable of detecting and classifying the spikes from multiple, simultaneously active neurons, even in situations where there is a high degree of spike waveform superposition on the recording channels. The protocols are based on the derivation of an optimal linear filter for each individual neuron. Each filter is tuned to selectively respond to the spike waveform generated by the corresponding neuron, and to attenuate noise and the spike waveforms from all other neurons. The protocol is essentially an extension of earlier work [1], [13], [18]. However, the protocols extend the power and utility of the original implementations in two significant respects. First, a general single-pass automatic template estimation algorithm was derived and implemented. Second, the filters were implemented within a software environment providing a greatly enhanced functional organization and user interface. The utility of the analysis approach was demonstrated on samples of multiunit electrophysiological recordings from the cricket abdominal nerve cord.
Optimal Linear Filters. 2. Pulse Time Measurements in the Presence of Noise
Energy Technology Data Exchange (ETDEWEB)
Nygaard, K.
1966-09-15
The problem of calculating the maximum available timing information contained in nuclear pulses in the presence of noise is solved theoretically. Practical experiments show that the theoretical values can be obtained by very simple, but untraditional, means. An output pulse from a practical filter connected to a charge sensitive amplifier with a Ge(Li) detector showed a rise time of 30 ns and a noise level of less than 5 keV. The time jitter measured was inversely proportional to the pulse height and less than 30 ns for 10 keV pulses. With the timing filter shown solid state detectors can be classified somewhere between Nal scintillators and organic scintillators with respect to time resolution.
Signal enhancement with variable span linear filters
Benesty, Jacob; Jensen, Jesper R
2016-01-01
This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of ...
Signal Enhancement with Variable Span Linear Filters
DEFF Research Database (Denmark)
Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Jesper Rindom
-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both......This book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed....... Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal...
Linearly constrained minimax optimization
DEFF Research Database (Denmark)
Madsen, Kaj; Schjær-Jacobsen, Hans
1978-01-01
We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...
Filters in topology optimization
DEFF Research Database (Denmark)
Bourdin, Blaise
1999-01-01
In this article, a modified (``filtered'') version of the minimum compliance topology optimization problem is studied. The direct dependence of the material properties on its pointwise density is replaced by a regularization of the density field using a convolution operator. In this setting...... it is possible to establish the existence of solutions. Moreover, convergence of an approximation by means of finite elements can be obtained. This is illustrated through some numerical experiments. The ``filtering'' technique is also shown to cope with two important numerical problems in topology optimization...
Filters in topology optimization
DEFF Research Database (Denmark)
Bourdin, Blaise
1999-01-01
In this article, a modified (``filtered'') version of the minimum compliance topology optimization problem is studied. The direct dependence of the material properties on its pointwise density is replaced by a regularization of the density field using a convolution operator. In this setting...... it is possible to establish the existence of solutions. Moreover, convergence of an approximation by means of finite elements can be obtained. This is illustrated through some numerical experiments. The ``filtering'' technique is also shown to cope with two important numerical problems in topology optimization...
Quantized, piecewise linear filter network
DEFF Research Database (Denmark)
Sørensen, John Aasted
1993-01-01
A quantization based piecewise linear filter network is defined. A method for the training of this network based on local approximation in the input space is devised. The training is carried out by repeatedly alternating between vector quantization of the training set into quantization classes an...
Distributed Fusion Receding Horizon Filtering in Linear Stochastic Systems
Directory of Open Access Journals (Sweden)
Il Young Song
2009-01-01
Full Text Available This paper presents a distributed receding horizon filtering algorithm for multisensor continuous-time linear stochastic systems. Distributed fusion with a weighted sum structure is applied to local receding horizon Kalman filters having different horizon lengths. The fusion estimate of the state of a dynamic system represents the optimal linear fusion by weighting matrices under the minimum mean square error criterion. The key contribution of this paper lies in the derivation of the differential equations for determining the error cross-covariances between the local receding horizon Kalman filters. The subsequent application of the proposed distributed filter to a linear dynamic system within a multisensor environment demonstrates its effectiveness.
Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique
Ouadi, Abderrahmane; Bentarzi, Hamid; Recioui, Abdelmadjid
2014-01-01
The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.
Linear Regression Based Real-Time Filtering
Directory of Open Access Journals (Sweden)
Misel Batmend
2013-01-01
Full Text Available This paper introduces real time filtering method based on linear least squares fitted line. Method can be used in case that a filtered signal is linear. This constraint narrows a band of potential applications. Advantage over Kalman filter is that it is computationally less expensive. The paper further deals with application of introduced method on filtering data used to evaluate a position of engraved material with respect to engraving machine. The filter was implemented to the CNC engraving machine control system. Experiments showing its performance are included.
Low Pass Filters with Linear Phase.
1985-12-12
DISCUSSION OF RESULTS............................... 35 LIST OF ILLUSTRATIONS Figure page 1. Template applicable to single stage linear phase filter .................. 2...technology suggests examination of the low-pass lin- ear phase filter as a means of prefiltering such data before, or concurrently with, sam- pling. Today, a...stage low passlinear phase filter . Here, M is the number of "main poles". A linear phase design alsorequires a minimum overhead of two "corrector poles
Optimization of integrated polarization filters
Gagnon, Denis; Déziel, Jean-Luc; Dubé, Louis J
2014-01-01
This study reports on the design of small footprint, integrated polarization filters based on engineered photonic lattices. Using a rods-in-air lattice as a basis for a TE filter and a holes-in-slab lattice for the analogous TM filter, we are able to maximize the degree of polarization of the output beams up to 98 % with a transmission efficiency greater than 75 %. The proposed designs allow not only for logical polarization filtering, but can also be tailored to output an arbitrary transverse beam profile. The lattice configurations are found using a recently proposed parallel tabu search algorithm for combinatorial optimization problems in integrated photonics.
Numerical Simulation of a Linear Filter.
1967-05-05
spectral density function . The study determines to what degree this method simulates a linear filter. Also included are correlation analyses of equidistributed sequences which are used in the method. (Author)
Inter modulation noise in trans linear filters
Energy Technology Data Exchange (ETDEWEB)
Martini, G.; Svelto, V. [Pavia Univ., Pavia (Italy). Dipt. di Elettronica
1999-06-01
The noise properties of trans linear filters operated in class A and class AB is examined, discussing how the output noise power depends on the circuit topology. It is shown that for in band useful signal the output noise does not depend on the relative position of the transistors in the filter.
Linear CMOS transconductance element for VHF filters
Nauta, B.; Seevinck, E.
1989-01-01
A differential transconductance element based on CMOS inverters is presented. With this circuit a linear, tunable integrator for very high-frequency continuous-time integrated filters can be made. This integrator has good linearity properties (THD<0.04%, Vipp=1.8 V), nondominant poles in the gigaher
Topics in computational linear optimization
DEFF Research Database (Denmark)
Hultberg, Tim Helge
2000-01-01
. Linear optimization problems covers both linear programming problems, which are polynomially solvable, and mixed integer linear programming problems, which belong to the class of NP-hard problems. The three main reasons for the practical succes of linear optimization are: wide applicability, availabilty...... of high quality solvers and the use of algebraic modelling systems to handle the communication between the modeller and the solver. This dissertation features four topics in computational linear optimization: A) automatic reformulation of mixed 0/1 linear programs, B) direct solution of sparse unsymmetric...... systems of linear equations, C) reduction of linear programs and D) integration of algebraic modelling of linear optimization problems in C++. Each of these topics is treated in a separate paper included in this dissertation. The efficiency of solving mixed 0-1 linear programs by linear programming based...
Filtering for linear systems with noise correlation and its application to singular systems
Institute of Scientific and Technical Information of China (English)
Wu Jian-Rong; Song Shi-Ji
2004-01-01
In this paper, an optimal filter for a stochastic linear system with previous stage noise correlation is designed.Based on this result, together with the decomposition techniques of the stochastic singular linear system, the design of an optimal filter for a stochastic singular linear system is given.
Topics in computational linear optimization
DEFF Research Database (Denmark)
Hultberg, Tim Helge
2000-01-01
of high quality solvers and the use of algebraic modelling systems to handle the communication between the modeller and the solver. This dissertation features four topics in computational linear optimization: A) automatic reformulation of mixed 0/1 linear programs, B) direct solution of sparse unsymmetric...... systems of linear equations, C) reduction of linear programs and D) integration of algebraic modelling of linear optimization problems in C++. Each of these topics is treated in a separate paper included in this dissertation. The efficiency of solving mixed 0-1 linear programs by linear programming based...... reductions. In the fourth and last paper, a prototype implementation of a C++ class library, FLOPC++, for formulating linear optimization problems is presented. Using FLOPC++, linear optimization models can be specified in a declarative style, similar to algebraic modelling languages such as GAMS and AMPL...
Linear filtering of systems with memory and application to finance
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available We study the linear filtering problem for systems driven by continuous Gaussian processes V ( 1 and V ( 2 with memory described by two parameters. The processes V ( j have the virtue that they possess stationary increments and simple semimartingale representations simultaneously. They allow for straightforward parameter estimations. After giving the semimartingale representations of V ( j by innovation theory, we derive Kalman-Bucy-type filtering equations for the systems. We apply the result to the optimal portfolio problem for an investor with partial observations. We illustrate the tractability of the filtering algorithm by numerical implementations.
An Asymptotic Analysis of the MIMO BC under Linear Filtering
Hunger, Raphael
2008-01-01
We investigate the MIMO broadcast channel in the high SNR regime when linear filtering is applied instead of dirty paper coding. Using a user-wise rate duality where the streams of every single user are not treated as self-interference as in the hitherto existing stream-wise rate dualities for linear filtering, we solve the weighted sum rate maximization problem of the broadcast channel in the dual multiple access channel. Thus, we can exactly quantify the asymptotic rate loss of linear filtering compared to dirty paper coding for any channel realization. Having converted the optimum covariance matrices to the broadcast channel by means of the duality, we observe that the optimal covariance matrices in the broadcast channel feature quite complicated but still closed form expressions although the respective transmit covariance matrices in the dual multiple access channel share a very simple structure. We immediately come to the conclusion that block-diagonalization is the asymptotically optimum transmit strate...
Optimal Nonlinear Filter for INS Alignment
Institute of Scientific and Technical Information of China (English)
赵瑞; 顾启泰
2002-01-01
All the methods to handle the inertial navigation system (INS) alignment were sub-optimal in the past. In this paper, particle filtering (PF) as an optimal method is used for solving the problem of INS alignment. A sub-optimal two-step filtering algorithm is presented to improve the real-time performance of PF. The approach combines particle filtering with Kalman filtering (KF). Simulation results illustrate the superior performance of these approaches when compared with extended Kalman filtering (EKF).
Optimal Robust Fault Detection for Linear Discrete Time Systems
Directory of Open Access Journals (Sweden)
Nike Liu
2008-01-01
Full Text Available This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as ℋ−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.
Topology optimization of microwave waveguide filters
Aage, Niels
2016-01-01
We present a density based topology optimization approach for the design of metallic microwave insert filters. A two-phase optimization procedure is proposed in which we, starting from a uniform design, first optimize to obtain a set of spectral varying resonators followed by a band gap optimization for the desired filter characteristics. This is illustrated through numerical experiments and comparison to a standard band pass filter design. It is seen that the carefully optimized topologies can sharpen the filter characteristics and improve performance. Furthermore, the obtained designs share little resemblance to standard filter layouts and hence the proposed design method offers a new design tool in microwave engineering.
Time signal filtering by relative neighborhood graph localized linear approximation
DEFF Research Database (Denmark)
Sørensen, John Aasted
1994-01-01
A time signal filtering algorithm based on the relative neighborhood graph (RNG) used for localization of linear filters is proposed. The filter is constructed from a training signal during two stages. During the first stage an RNG is constructed. During the second stage, localized linear filters...
Sensitivity Limitations for Multivariable Linear Filtering
Directory of Open Access Journals (Sweden)
Steven R. Weller
2007-01-01
Full Text Available This paper examines fundamental limitations in performance which apply to linear filtering problems associated with multivariable systems having as many inputs as outputs. The results of this paper quantify unavoidable limitations in the sensitivity of state estimates to process and measurement disturbances, as represented by the maximum singular values of the relevant transfer matrices. These limitations result from interpolation constraints imposed by open right half-plane poles and zeros in the transfer matrices linking process noise and output noise with state estimates. Using the Poisson integral inequality, this paper shows how sensitivity limitations and tradeoffs in multivariable filtering problems are intimately related to the directionality properties of the open right half-plane poles and zeros in these transfer matrices.
Optimal control linear quadratic methods
Anderson, Brian D O
2007-01-01
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory from an engineering viewpoint, with step-by-step explanations that show clearly how to make practical use of the material.The three-part treatment begins with the basic theory of the linear regulator/tracker for time-invariant and time-varying systems. The Hamilton-Jacobi equation is introduced using the Principle of Optimality, and the infinite-time problem is considered. The second part outlines the
An optimal noise reduction linear phase filter banks based on FPGA%一种最优去噪线性相位滤波器组的FPGA实现
Institute of Scientific and Technical Information of China (English)
张辉
2011-01-01
To desip an oversampled linear phase perfect reconstruction filter banks with lattice structure is an efficient implementation. Once the analysis filter banks are ensured, the structure of synthesis filter banks is determined, but there is still lots of synthesis filter banks for the parameters are flexible, in which choose a synthesis filter banks for optimal noise reduction. This paper implements the design in FPGA with DSP Builder, and simulate the design on function with Modelsim.%格型结构是一种可以快速高效设计过采样线性相位完全重建滤波器组的方法.一旦分析滤波器组设定后,对应的综合滤波器结构也就确定,但综合滤波器组参数却有很大的灵活性,从中可以找出具有最优去噪效果的综合滤波器组,构成一个完整的滤波器组.对于求解出的具有最优去噪效果的过采样线性相位完全重构滤波器组,文中用DSP Builder在FPGA上予以实现,并用modelsim进行功能仿真.
Design Techniques for Uniform-DFT, Linear Phase Filter Banks
Sun, Honglin; DeLeon, Phillip
1999-01-01
Uniform-DFT filter banks are an important class of filter banks and their theory is well known. One notable characteristic is their very efficient implementation when using polyphase filters and the FFT. Separately, linear phase filter banks, i.e. filter banks in which the analysis filters have a linear phase are also an important class of filter banks and desired in many applications. Unfortunately, it has been proved that one cannot design critically-sampled, uniform-DFT, linear phase filter banks and achieve perfect reconstruction. In this paper, we present a least-squares solution to this problem and in addition prove that oversampled, uniform-DFT, linear phase filter banks (which are also useful in many applications) can be constructed for perfect reconstruction. Design examples are included illustrate the methods.
Satisfactory Optimization Design of IIR Digital Filters
Institute of Scientific and Technical Information of China (English)
Jin Weidong; Zhang Gexiang; Zhao Duo
2005-01-01
A new method called satisfactory optimization method is proposed to design IIR (Infinite Impulse Response) digital filters, and the satisfactory optimization model is presented. The detailed algorithm of designing IIR digital filters using satisfactory optimization method is described. By using quantum genetic algorithm characterized by rapid convergence and good global search capability, the satisfying solutions are achieved in the experiment of designing lowpass and bandpass IIR digital filters. Experimental results show that the performances of IIR filters designed by the introduced method are better than those by traditional methods.
A family of quantization based piecewise linear filter networks
DEFF Research Database (Denmark)
Sørensen, John Aasted
1992-01-01
A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization of...
Undithering using linear filtering and non-linear diffusion techniques
Asha, V
2011-01-01
Data compression is a method of improving the efficiency of transmission and storage of images. Dithering, as a method of data compression, can be used to convert an 8-bit gray level image into a 1-bit / binary image. Undithering is the process of reconstruction of gray image from binary image obtained from dithering of gray image. In the present paper, I propose a method of undithering using linear filtering followed by anisotropic diffusion which brings the advantage of smoothing and edge enhancement. First-order statistical parameters, second-order statistical parameters, mean-squared error (MSE) between reconstructed image and the original image before dithering, and peak signal to noise ratio (PSNR) are evaluated at each step of diffusion. Results of the experiments show that the reconstructed image is not as sharp as the image before dithering but a large number of gray values are reproduced with reference to those of the original image prior to dithering.
Linear Phase Perfect Reconstruction Filters and Wavelets with Even Symmetry
Monzon, Lucas
2011-01-01
Perfect reconstruction filter banks can be used to generate a variety of wavelet bases. Using IIR linear phase filters one can obtain symmetry properties for the wavelet and scaling functions. In this paper we describe all possible IIR linear phase filters generating symmetric wavelets with any prescribed number of vanishing moments. In analogy with the well known FIR case, we construct and study a new family of wavelets obtained by considering maximal number of vanishing moments for each fixed order of the IIR filter. Explicit expressions for the coefficients of numerator, denominator, zeroes, and poles are presented. This new parameterization allows one to design linear phase quadrature mirror filters with many other properties of interest such as filters that have any preassigned set of zeroes in the stopband or that satisfy an almost interpolating property. Using Beylkin's approach, it is indicated how to implement these IIR filters not as recursive filters but as FIR filters.
Model based optimization of EMC input filters
Energy Technology Data Exchange (ETDEWEB)
Raggl, K; Kolar, J. W. [Swiss Federal Institute of Technology, Power Electronic Systems Laboratory, Zuerich (Switzerland); Nussbaumer, T. [Levitronix GmbH, Zuerich (Switzerland)
2008-07-01
Input filters of power converters for compliance with regulatory electromagnetic compatibility (EMC) standards are often over-dimensioned in practice due to a non-optimal selection of number of filter stages and/or the lack of solid volumetric models of the inductor cores. This paper presents a systematic filter design approach based on a specific filter attenuation requirement and volumetric component parameters. It is shown that a minimal volume can be found for a certain optimal number of filter stages for both the differential mode (DM) and common mode (CM) filter. The considerations are carried out exemplarily for an EMC input filter of a single phase power converter for the power levels of 100 W, 300 W, and 500 W. (author)
A Controlled Particle Filter for Global Optimization
Zhang, Chi; Taghvaei, Amirhossein; Mehta, Prashant G.
2017-01-01
A particle filter is introduced to numerically approximate a solution of the global optimization problem. The theoretical significance of this work comes from its variational aspects: (i) the proposed particle filter is a controlled interacting particle system where the control input represents the solution of a mean-field type optimal control problem; and (ii) the associated density transport is shown to be a gradient flow (steepest descent) for the optimal value function, with respect to th...
Linear filtering of images based on properties of vision.
Algazi, V R; Ford, G E; Chen, H
1995-01-01
The design of linear image filters based on properties of human visual perception has been shown to require the minimization of criterion functions in both the spatial and frequency domains. We extend this approach to continuous filters of infinite support. For lowpass filters, this leads to the concept of an ideal lowpass image filter that provides a response that is superior perceptually to that of the classical ideal lowpass filter.
Automatic Target Detection by Optimal Morphological Filters
Institute of Scientific and Technical Information of China (English)
YU Nong(余农); WU Hao(吴昊); WU ChangYong(吴常泳); LI YuShu(李予蜀)
2003-01-01
It is widely accepted that the design of morphological filters, which are optimal in some sense, is a difficult task. In this paper a novel method for optimal learning of morphological filtering parameters (Genetic training algorithm for morphological filters, GTAMF) is presented.GTAMF adopts new crossover and mutation operators called the curved cylinder crossover and master-slave mutation to achieve optimal filtering parameters in a global searching. Experimental results show that this method is practical, easy to extend, and markedly improves the performances of morphological filters. The operation of a morphological filter can be divided into two basic problems including morphological operation and structuring element (SE) selection. The rules for morphological operations are predefined so that the filter's properties depend merely on the selection of SE. By means of adaptive optimization training, structuring elements possess the shape and structural characteristics of image targets, and give specific information to SE. Morphological filters formed in this way become certainly intelligent and can provide good filtering results and robust adaptability to image targets with clutter background.
Applications of Kalman filters based on non-linear functions to numerical weather predictions
Directory of Open Access Journals (Sweden)
G. Galanis
2006-10-01
Full Text Available This paper investigates the use of non-linear functions in classical Kalman filter algorithms on the improvement of regional weather forecasts. The main aim is the implementation of non linear polynomial mappings in a usual linear Kalman filter in order to simulate better non linear problems in numerical weather prediction. In addition, the optimal order of the polynomials applied for such a filter is identified. This work is based on observations and corresponding numerical weather predictions of two meteorological parameters characterized by essential differences in their evolution in time, namely, air temperature and wind speed. It is shown that in both cases, a polynomial of low order is adequate for eliminating any systematic error, while higher order functions lead to instabilities in the filtered results having, at the same time, trivial contribution to the sensitivity of the filter. It is further demonstrated that the filter is independent of the time period and the geographic location of application.
Topology optimization of microwave waveguide filters
DEFF Research Database (Denmark)
Aage, Niels; Johansen, Villads Egede
2017-01-01
We present a density based topology optimization approach for the design of metallic microwave insert filters. A two-phase optimization procedure is proposed in which we, starting from a uniform design, first optimize to obtain a set of spectral varying resonators followed by a band gap optimizat......We present a density based topology optimization approach for the design of metallic microwave insert filters. A two-phase optimization procedure is proposed in which we, starting from a uniform design, first optimize to obtain a set of spectral varying resonators followed by a band gap...... little resemblance to standard filter layouts and hence the proposed design method offers a new design tool in microwave engineering....
ECG baseline wander reduction using linear phase filters
Alsté, van J.A.; Eck, van W.; Hermann, O.E.
1986-01-01
The continuous real time reduction of baseline wander is a considerable problem in electrocardiography during exercises. Our solution consists of spectral filtering. The legitimacy of high-pass filtering of the ECG by means of digital linear phase filters with a low cut-off frequency as high as the
Discrete stochastic processes and optimal filtering
Bertein, Jean-Claude
2012-01-01
Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which ar
Institute of Scientific and Technical Information of China (English)
冯尚明; 杨波
2009-01-01
A speed estimation method of linear induction motor(LIM) using a novel extended kalman filter(EKF) was presented in this paper. The modification for dynamic end effect of LIM was designed to achieve exact estimation results when LIM ran at high speed. A new approach of optimizing the performance of the extended kalman filter using simulated annealing genetic algorithm (SAGA) was compared with the use of a genetic algorithm(GA). The optimization techniques are verified effective by simulation on a field-oriented controller under various operating conditions including motor parame-ter sensitivity and load disturbance.%采用一种新颖的扩展卡尔曼滤波器(EKF)实现了对直线感应电动机的速度检测,并考虑边端效应的影响进行了修正.采用模拟退火遗传算法(SAGA)对EKF性能进行优化,并与遗传算法(GA)优化的EKF进行了比较,表明SAGA具有更强的寻优能力.包括电机参数变化、负载扰动等情况下的仿真结果证明了该方案的有效性.
Optimal Filtering of Malicious IP Sources
Soldo, Fabio; Argyraki, Katerina
2008-01-01
How can we protect the network infrastructure from malicious traffic, such as scanning, malicious code propagation, and distributed denial-of-service (DDoS) attacks? One mechanism for blocking malicious traffic is filtering: access control lists (ACLs) can selectively block traffic based on fields of the IP header. Filters (ACLs) are already available in the routers today but are a scarce resource because they are stored in the expensive ternary content addressable memory (TCAM). In this paper, we develop, for the first time, a framework for studying filter selection as a resource allocation problem. Within this framework, we study five practical cases of source address/prefix filtering, which correspond to different attack scenarios and operator's policies. We show that filter selection optimization leads to novel variations of the multidimensional knapsack problem and we design optimal, yet computationally efficient, algorithms to solve them. We also evaluate our approach using data from Dshield.org and dem...
[Radiation dose reduction using a non-linear image filter in MDCT].
Nakashima, Junya; Takahashi, Toshiyuki; Takahashi, Yoshimasa; Imai, Yasuhiro; Ishihara, Yotaro; Kato, Kyoichi; Nakazawa, Yasuo
2010-05-20
The development of MDCT enabled various high-quality 3D imaging and optimized scan timing with contrast injection in a multi-phase dynamic study. Since radiation dose tends to increase to yield such high-quality images, we have to make an effort to reduce radiation dose. A non-linear image filter (Neuro 3D filter: N3D filter) has been developed in order to improve image noise. The purpose of this study was to evaluate the physical performance and effectiveness of this non-linear image filter using phantoms, and show how we can reduce radiation dose in clinical use of this filter. This N3D filter reduced radiation dose by about 50%, with minimum deterioration of spatial reduction in phantom and clinical studies. This filter shows great potential for clinical application.
Design of Optimal Quincunx Filter Banks for Image Coding
Directory of Open Access Journals (Sweden)
Wu-Sheng Lu
2007-01-01
Full Text Available Two new optimization-based methods are proposed for the design of high-performance quincunx filter banks for the application of image coding. These new techniques are used to build linear-phase finite-length-impulse-response (FIR perfect-reconstruction (PR systems with high coding gain, good frequency selectivity, and certain prescribed vanishing-moment properties. A parametrization of quincunx filter banks based on the lifting framework is employed to structurally impose the PR and linear-phase conditions. Then, the coding gain is maximized subject to a set of constraints on vanishing moments and frequency selectivity. Examples of filter banks designed using the newly proposed methods are presented and shown to be highly effective for image coding. In particular, our new optimal designs are shown to outperform three previously proposed quincunx filter banks in 72% to 95% of our experimental test cases. Moreover, in some limited cases, our optimal designs are even able to outperform the well-known (separable 9/7 filter bank (from the JPEG-2000 standard.
Design of H(infinity) robust fault detection filter for linear uncertain time-delay systems.
Bai, Leishi; Tian, Zuohua; Shi, Songjiao
2006-10-01
In this paper, the robust fault detection filter design problem for linear time-delay systems with both unknown inputs and parameter uncertainties is studied. Using a multiobjective optimization technique, a new performance index is introduced, which takes into account the robustness of the fault detection filter against disturbances and sensitivity to faults simultaneously. The reference residual model is then designed based on this performance index to formulate the robust fault detection filter design problem as an H(infinity) model-matching problem. By applying robust H(infinity) optimization control technique, the existence condition of the robust fault detection filter for linear time-delay systems with both unknown inputs and parameter uncertainties is presented in terms of linear matrix inequality formulation, independently of time delay. In order to detect the fault, an adaptive threshold which depends on the inputs is finally determined. An illustrative design example is used to demonstrate the validity of the proposed approach.
Gravitation search algorithm: Application to the optimal IIR filter design
Directory of Open Access Journals (Sweden)
Suman Kumar Saha
2014-01-01
Full Text Available This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA for the design of 8th order Infinite Impulse Response (IIR, low pass (LP, high pass (HP, band pass (BP and band stop (BS filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA and standard Particle Swarm Optimization (PSO. Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability.
Computing the Matched Filter in Linear Time
Fish, Alexander; Hadani, Ronny; Sayeed, Akbar; Schwartz, Oded
2011-01-01
A fundamental problem in wireless communication is the time-frequency shift (TFS) problem: Find the time-frequency shift of a signal in a noisy environment. The shift is the result of time asynchronization of a sender with a receiver, and of non-zero speed of a sender with respect to a receiver. A classical solution of a discrete analog of the TFS problem is called the matched filter algorithm. It uses a pseudo-random waveform S(t) of the length p, and its arithmetic complexity is O(p^{2} \\cdot log (p)), using fast Fourier transform. In these notes we introduce a novel approach of designing new waveforms that allow faster matched filter algorithm. We use techniques from group representation theory to design waveforms S(t), which enable us to introduce two fast matched filter (FMF) algorithms, called the flag algorithm, and the cross algorithm. These methods solve the TFS problem in O(p\\cdot log (p)) operations. We discuss applications of the algorithms to mobile communication, GPS, and radar.
Desensitized Optimal Filtering and Sensor Fusion Toolkit
Karlgaard, Christopher D.
2015-01-01
Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.
On Alternative Optimal Solutions to Linear Fractional Optimization Problems
Institute of Scientific and Technical Information of China (English)
ShengjiaXue
2004-01-01
The structure of the optimal solution set is derived for linear fractional optimization problems with the representation theorem of polyhedral sets．And the computational procedure in determining all optimal solutions is also given．
Desensitized Optimal Filtering and Sensor Fusion Tool Kit Project
National Aeronautics and Space Administration — Research on desensitized optimal filtering techniques and a navigation and sensor fusion tool kit using advanced filtering techniques is proposed. Research focuses...
Outbound SPIT Filter with Optimal Performance Guarantees
Jung, Tobias; Nassar, Mohamed; Ernst, Damien; Leduc, Guy
2012-01-01
This paper presents a formal framework for identifying and filtering SPIT calls (SPam in Internet Telephony) in an outbound scenario with provable optimal performance. In so doing, our work is largely different from related previous work: our goal is to rigorously formalize the problem in terms of mathematical decision theory, find the optimal solution to the problem, and derive concrete bounds for its expected loss (number of mistakes the SPIT filter will make in the worst case). This goal is achieved by considering an abstracted scenario amenable to theoretical analysis, namely SPIT detection in an outbound scenario with pure sources. Our methodology is to first define the cost of making an error (false positive and false negative), apply Wald's sequential probability ratio test to the individual sources, and then determine analytically error probabilities such that the resulting expected loss is minimized. The benefits of our approach are: (1) the method is optimal (in a sense defined in the paper); (2) th...
On filter boundary conditions in topology optimization
DEFF Research Database (Denmark)
Clausen, Anders; Andreassen, Erik
2017-01-01
we define three requirements that boundary conditions must fulfill in order to eliminate boundary effects. Previously suggested approaches are briefly reviewed in the light of these requirements. A new approach referred to as the “domain extension approach” is suggested. It effectively eliminates......Most research papers on topology optimization involve filters for regularization. Typically, boundary effects from the filters are ignored. Despite significant drawbacks the inappropriate homogeneous Neumann boundary conditions are used, probably because they are trivial to implement. In this paper...
Shen, Sylvia S.; Miller, David P.; Lewis, Paul E.
2010-08-01
Linear variable filter design and fabrication for LWIR is now commercially available for use in the development of airborne reconnaissance or surveillance systems. The linear variable filter is attached directly to the cold shield of the focal plane array. The resulting compact spectrometer assemblies are completely contained in the Dewar system. This approach eliminates many of the wavelength calibration problems associated with current prism and grating systems and also facilitates the cost effective design and fabrication of aerial sensing systems for specific applications. An optimal 32 band linear-variablefilter- based system for detecting and discriminating a set of 11 chemicals representing a high probability of occurrence during a typical emergency response chemical incident was determined in a companion paper entitled "Linear Variable Filter Optimization for Emergency Response Chemical Detection and Discrimination". This paper addresses the effects of atmospheric water vapor on the performance of this optimal 32 band linear-variable-filter-based system. This paper also determines at what increased concentration levels above the optimal system design goal of 30 ppm-m can detection and discrimination of these 11 chemicals be achieved in realistic but imperfect atmospheric water vapor removal scenarios.
On filter-successive linearization methods for nonlinear semidefinite programming
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially effcient.
On filter-successive linearization methods for nonlinear semidefinite programming
Institute of Scientific and Technical Information of China (English)
LI ChengJin; SUN WenYui
2009-01-01
In this paper we present a filter-successive linearization method with trust region for solutions of nonlinear semidefinite programming. Such a method is based on the concept of filter for nonlinear programming introduced by Fletcher and Leyffer in 2002. We describe the new algorithm and prove its global convergence under weaker assumptions. Some numerical results are reported and show that the new method is potentially efficient.
When "Optimal Filtering" Isn't
Fowler, J W; Doriese, W B; Hays-Wehle, J; Joe, Y -I; Morgan, K M; O'Neil, G C; Reintsema, C D; Schmidt, D R; Ullom, J N; Swetz, D S
2016-01-01
The so-called "optimal filter" analysis of a microcalorimeter's x-ray pulses is statistically optimal only if all pulses have the same shape, regardless of energy. The shapes of pulses from a nonlinear detector can and do depend on the pulse energy, however. A pulse-fitting procedure that we call "tangent filtering" accounts for the energy dependence of the shape and should therefore achieve superior energy resolution. We take a geometric view of the pulse-fitting problem and give expressions to predict how much the energy resolution stands to benefit from such a procedure. We also demonstrate the method with a case study of K-line fluorescence from several 3d transition metals. The method improves the resolution from 4.9 eV to 4.2 eV at the Cu K$\\alpha$ line (8.0keV).
A brief overview of speech enhancement with linear filtering
DEFF Research Database (Denmark)
Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Jesper Rindom;
2014-01-01
In this paper, we provide an overview of some recently introduced principles and ideas for speech enhancement with linear filtering and explore how these are related and how they can be used in various applications. This is done in a general framework where the speech enhancement problem is stated......-to-noise ratio (SNR), and Wiener filters are derived from the conventional speech enhancement approach and the recently introduced orthogonal decomposition approach. For each of the filters, we derive their properties in terms of output SNR and speech distortion. We then demonstrate how the ideas can be applied...
Identification of linear stochastic systems through projection filters
Chen, Chung-Wen; Huang, Jen-Kuang; Juang, Jer-Nan
1992-01-01
A novel method is presented for identifying a state-space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relationship between the state-space model and the finite-difference model of linear stochastic systems derived through projection filters. It is proved that least-squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model.
Linear Tabling Strategies and Optimizations
Zhou, Neng-Fa; Shen, Yi-Dong
2007-01-01
Recently, the iterative approach named linear tabling has received considerable attention because of its simplicity, ease of implementation, and good space efficiency. Linear tabling is a framework from which different methods can be derived based on the strategies used in handling looping subgoals. One decision concerns when answers are consumed and returned. This paper describes two strategies, namely, {\\it lazy} and {\\it eager} strategies, and compares them both qualitatively and quantitatively. The results indicate that, while the lazy strategy has good locality and is well suited for finding all solutions, the eager strategy is comparable in speed with the lazy strategy and is well suited for programs with cuts. Linear tabling relies on depth-first iterative deepening rather than suspension to compute fixpoints. Each cluster of inter-dependent subgoals as represented by a top-most looping subgoal is iteratively evaluated until no subgoal in it can produce any new answers. Naive re-evaluation of all loopi...
Group Lifting Structures For Multirate Filter Banks, II: Linear Phase Filter Banks
Energy Technology Data Exchange (ETDEWEB)
Brislawn, Christopher M [Los Alamos National Laboratory
2008-01-01
The theory of group lifting structures is applied to linear phase lifting factorizations for the two nontrivial classes of two-channel linear phase perfect reconstruction filter banks, the whole-and half-sample symmetric classes. Group lifting structures defined for the reversible and irreversible classes of whole-and half-sample symmetric filter banks are shown to satisfy the hypotheses of the uniqueness theorem for group lifting structures. It follows that linear phase lifting factorizations of whole-and half-sample symmetric filter banks are therefore independent of the factorization methods used to compute them. These results cover the specification of user-defined whole-sample symmetric filter banks in Part 2 of the ISO JPEG 2000 standard.
Optimal Sensor Decision Based on Particle Filter
Institute of Scientific and Technical Information of China (English)
XU Meng; WANG Hong-wei; HU Shi-qiang
2006-01-01
A novel infrared and radar synergistic tracking algorithm, which is based on the idea of closed loop control, and target's motion model identification and particle filter approach, was put forward. In order to improve the observability and filtering divergence of infrared search and tracking, the unscented Kalman filter algorithm that has stronger ability of non-linear approximation was adopted. The polynomial and least square method based on radar and IRST measurements to identify the parameters of the model was proposed, and a "pseudo sensor" was suggested to estimate the target position according to the identified model even if the radar is turned off. At last,the average Kullback-Leibler discrimination distance based on particle filter was used to measure the tracking performance, based on tracking performance and fuzzy stochastic decision, the idea of closed loop was used to retrieve the module parameter of "pseudo sensor". The experimental result indicates that the algorithm can not only limit the radar activity effectively but also keep the tracking accuracy of active/passive system well.
Filtering nonlinear dynamical systems with linear stochastic models
Harlim, J.; Majda, A. J.
2008-06-01
An important emerging scientific issue is the real time filtering through observations of noisy signals for nonlinear dynamical systems as well as the statistical accuracy of spatio-temporal discretizations for filtering such systems. From the practical standpoint, the demand for operationally practical filtering methods escalates as the model resolution is significantly increased. For example, in numerical weather forecasting the current generation of global circulation models with resolution of 35 km has a total of billions of state variables. Numerous ensemble based Kalman filters (Evensen 2003 Ocean Dyn. 53 343-67 Bishop et al 2001 Mon. Weather Rev. 129 420-36 Anderson 2001 Mon. Weather Rev. 129 2884-903 Szunyogh et al 2005 Tellus A 57 528-45 Hunt et al 2007 Physica D 230 112-26) show promising results in addressing this issue; however, all these methods are very sensitive to model resolution, observation frequency, and the nature of the turbulent signals when a practical limited ensemble size (typically less than 100) is used. In this paper, we implement a radical filtering approach to a relatively low (40) dimensional toy model, the L-96 model (Lorenz 1996 Proc. on Predictability (ECMWF, 4-8 September 1995) pp 1-18) in various chaotic regimes in order to address the 'curse of ensemble size' for complex nonlinear systems. Practically, our approach has several desirable features such as extremely high computational efficiency, filter robustness towards variations of ensemble size (we found that the filter is reasonably stable even with a single realization) which makes it feasible for high dimensional problems, and it is independent of any tunable parameters such as the variance inflation coefficient in an ensemble Kalman filter. This radical filtering strategy decouples the problem of filtering a spatially extended nonlinear deterministic system to filtering a Fourier diagonal system of parametrized linear stochastic differential equations (Majda and Grote
Improved H_∞ filtering for Markov jumping linear systems with non-accessible mode information
Institute of Scientific and Technical Information of China (English)
GUO YaFeng; LI ShaoYuan
2009-01-01
This paper is concerned with the H_∞ filtering problems for both continuous-and discrete-time Markov jumping linear systems (MJLS) with non-accessible mode Information.A new design method is proposed,which greatly reduces the overdesign Introduced in the derivation process.The desired filters can be obtained from the solution of convex optimization problems in terms of linear matrix inequalities (LMIs),which can be solved via efficient interior-point algorithms.Numerical examples are provided to Illustrate the advantages of the proposed approach.
Optimal social insurance with linear income taxation
DEFF Research Database (Denmark)
Bovenberg, Lans; Sørensen, Peter Birch
2009-01-01
We study optimal social insurance aimed at insuring disability risk in the presence of linear income taxation. Optimal disability insurance benefits rise with previous earnings. Optimal insurance is incomplete even though disability risks are exogenous and verifiable so that moral hazard...... in disability insurance is absent. Imperfect insurance is optimal because it encourages workers to insure themselves against disability by working and saving more, thereby alleviating the distortionary impact of the redistributive income tax on labor supply and savings....
Weighted-Sum-Rate-Maximizing Linear Transceiver Filters for the K-User MIMO Interference Channel
Shin, Joonwoo
2012-01-01
This letter is concerned with transmit and receive filter optimization for the K-user MIMO interference channel. Specifically, linear transmit and receive filter sets are designed which maximize the weighted sum rate while allowing each transmitter to utilize only the local channel state information. Our approach is based on extending the existing method of minimizing the weighted mean squared error (MSE) for the MIMO broadcast channel to the K-user interference channel at hand. For the case of the individual transmitter power constraint, however, a straightforward generalization of the existing method does not reveal a viable solution. It is in fact shown that there exists no closed-form solution for the transmit filter but simple one-dimensional parameter search yields the desired solution. Compared to the direct filter optimization using gradient-based search, our solution requires considerably less computational complexity and a smaller amount of feedback resources while achieving essentially the same lev...
FUZZY OPTIMIZATION USING EXTENDED KALMAN FILTER
Directory of Open Access Journals (Sweden)
M.DIVYA
2013-01-01
Full Text Available Fuzzy Logic is based on the idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not only 0 or 1, as in crisp set theory. The degree of membership function is defined as the gradation in the extent to which an element is belonging to the relevant sets. Optimizing the membership functions of a fuzzy system can be viewed as a system identification problem for nonlinear dynamic system. In this paper two input and one output fuzzy controller is designed for the dynamic process of aircraft. The addition of an EKF in the feedback loop improved the system response by blocking possible effects of measurement error based on Predictor-Corrector algorithm. An Extended Kalman Filter approach to optimize the membership functions of the inputs and outputs of the fuzzy controller. The performance of the fuzzy system before and after the optimization are compared, as well as the membership functions.
Linear and nonlinear filters under high power microwave conditions
Directory of Open Access Journals (Sweden)
F. Brauer
2009-05-01
Full Text Available The development of protection circuits against a variety of electromagnetic disturbances is important to assure the immunity of an electronic system. In this paper the behavior of linear and nonlinear filters is measured and simulated with high power microwave (HPM signals to achieve a comprehensive protection against different high power electromagnetic (HPEM threats.
Spectral measurement using IC-compatible linear variable optical filter
Emadi, A.; Grabarnik, S.; Wu, H.; De Graaf, G.; Hedsten, K.; Enoksson, P.; Correia, J.H.; Wolffenbuttel, R.F.
2010-01-01
This paper reports on the functional and spectral characterization of a microspectrometer based on a CMOS detector array covered by an IC-Compatible Linear Variable Optical Filter (LVOF). The Fabry-Perot LVOF is composed of 15 dielectric layers with a tapered middle cavity layer, which has been
Energy Technology Data Exchange (ETDEWEB)
Park, M.G.; Kim, Y.H.; Cha, K.H.; Kim, M.K. [Korea Electric Power Research Institute, Taejon (Korea)
1999-07-01
A method is described to develop and H{infinity} filtering method for the dynamic compensation of self-powered neutron detectors normally used for fixed incore instruments. An H{infinity} norm of the filter transfer matrix is used as the optimization criteria in the worst-case estimation error sense. Filter modeling is performed for both continuous- and discrete-time models. The filter gains are optimized in the sense of noise attenuation level of H{infinity} setting. By introducing Bounded Real Lemma, the conventional algebraic Riccati inequalities are converted into Linear Matrix Inequalities (LMIs). Finally, the filter design problem is solved via the convex optimization framework using LMIs. The simulation results show that remarkable improvements are achieved in view of the filter response time and the filter design efficiency. (author). 15 refs., 4 figs., 3 tabs.
GNSS data filtering optimization for ionospheric observation
D'Angelo, G.; Spogli, L.; Cesaroni, C.; Sgrigna, V.; Alfonsi, L.; Aquino, M. H. O.
2015-12-01
In the last years, the use of GNSS (Global Navigation Satellite Systems) data has been gradually increasing, for both scientific studies and technological applications. High-rate GNSS data, able to generate and output 50-Hz phase and amplitude samples, are commonly used to study electron density irregularities within the ionosphere. Ionospheric irregularities may cause scintillations, which are rapid and random fluctuations of the phase and the amplitude of the received GNSS signals. For scintillation analysis, usually, GNSS signals observed at an elevation angle lower than an arbitrary threshold (usually 15°, 20° or 30°) are filtered out, to remove the possible error sources due to the local environment where the receiver is deployed. Indeed, the signal scattered by the environment surrounding the receiver could mimic ionospheric scintillation, because buildings, trees, etc. might create diffusion, diffraction and reflection. Although widely adopted, the elevation angle threshold has some downsides, as it may under or overestimate the actual impact of multipath due to local environment. Certainly, an incorrect selection of the field of view spanned by the GNSS antenna may lead to the misidentification of scintillation events at low elevation angles. With the aim to tackle the non-ionospheric effects induced by multipath at ground, in this paper we introduce a filtering technique, termed SOLIDIFY (Standalone OutLiers IDentIfication Filtering analYsis technique), aiming at excluding the multipath sources of non-ionospheric origin to improve the quality of the information obtained by the GNSS signal in a given site. SOLIDIFY is a statistical filtering technique based on the signal quality parameters measured by scintillation receivers. The technique is applied and optimized on the data acquired by a scintillation receiver located at the Istituto Nazionale di Geofisica e Vulcanologia, in Rome. The results of the exercise show that, in the considered case of a noisy
Consensus+Innovations Distributed Kalman Filter With Optimized Gains
Das, Subhro; Moura, Jose M. F.
2017-01-01
In this paper, we address the distributed filtering and prediction of time-varying random fields represented by linear time-invariant (LTI) dynamical systems. The field is observed by a sparsely connected network of agents/sensors collaborating among themselves. We develop a Kalman filter type consensus+innovations distributed linear estimator of the dynamic field termed as Consensus+Innovations Kalman Filter. We analyze the convergence properties of this distributed estimator. We prove that the mean-squared error of the estimator asymptotically converges if the degree of instability of the field dynamics is within a pre-specified threshold defined as tracking capacity of the estimator. The tracking capacity is a function of the local observation models and the agent communication network. We design the optimal consensus and innovation gain matrices yielding distributed estimates with minimized mean-squared error. Through numerical evaluations, we show that, the distributed estimator with optimal gains converges faster and with approximately 3dB better mean-squared error performance than previous distributed estimators.
Can linear superiorization be useful for linear optimization problems?
Censor, Yair
2017-04-01
Linear superiorization (LinSup) considers linear programming problems but instead of attempting to solve them with linear optimization methods it employs perturbation resilient feasibility-seeking algorithms and steers them toward reduced (not necessarily minimal) target function values. The two questions that we set out to explore experimentally are: (i) does LinSup provide a feasible point whose linear target function value is lower than that obtained by running the same feasibility-seeking algorithm without superiorization under identical conditions? (ii) How does LinSup fare in comparison with the Simplex method for solving linear programming problems? Based on our computational experiments presented here, the answers to these two questions are: ‘yes’ and ‘very well’, respectively.
On optimal filtering of measured Mueller matrices
Gil, Jose J
2016-01-01
While any two-dimensional mixed state of polarization of light can be represented by a combination of a pure state and a fully random state, any Mueller matrix can be represented by a convex combination of a pure component and three additional components whose randomness is scaled in a proper and objective way. Such characteristic decomposition constitutes the appropriate framework for the characterization of the polarimetric randomness of the system represented by a given Mueller matrix, and provides appropriate criteria for the optimal filtering of noise in experimental polarimetry.
Kalman filtering for time-delayed linear systems
Institute of Scientific and Technical Information of China (English)
LU Xiao; WANG Wei
2006-01-01
This paper is to study the linear minimum variance estimation for discrete- time systems. A simple approach to the problem is presented by developing re-organized innovation analysis for the systems with instantaneous and double time-delayed measurements. It is shown that the derived estimator involves solving three different standard Kalman filtering with the same dimension as the original system. The obtained results form the basis for solving some complicated problems such as H∞ fixed-lag smoothing, preview control, H∞ filtering and control with time delays.
Directory of Open Access Journals (Sweden)
Jan eKneissler
2015-04-01
Full Text Available Predictive coding appears to be one of the fundamental working principles of brain processing. Amongst other aspects, brains often predict the sensory consequences of their own actions. Predictive coding resembles Kalman filtering, where incoming sensory information is filtered to produce prediction errors for subsequent adaptation and learning. However, to generate prediction errors given motor commands, a suitable temporal forward model is required to generate predictions. While in engineering applications, it is usually assumed that this forward model is known, the brain has to learn it. When filtering sensory input and learning from the residual signal in parallel, a fundamental problem arises: the system can enter a delusional loop when filtering the sensory information using an overly trusted forward model. In this case, learning stalls before accurate convergence because uncertainty about the forward model is not properly accommodated. We present a Bayes-optimal solution to this generic and pernicious problem for the case of linear forward models, which we call Predictive Inference and Adaptive Filtering (PIAF. PIAF filters incoming sensory information and learns the forward model simultaneously. We show that PIAF is formally related to Kalman filtering and to the Recursive Least Squares linear approximation method, but combines these procedures in a Bayes optimal fashion. Numerical evaluations confirm that the delusional loop is precluded and that the learning of the forward model is more than ten-times faster when compared to a naive combination of Kalman filtering and Recursive Least Squares.
Optimal subband Kalman filter for normal and oesophageal speech enhancement.
Ishaq, Rizwan; García Zapirain, Begoña
2014-01-01
This paper presents the single channel speech enhancement system using subband Kalman filtering by estimating optimal Autoregressive (AR) coefficients and variance for speech and noise, using Weighted Linear Prediction (WLP) and Noise Weighting Function (NWF). The system is applied for normal and Oesophageal speech signals. The method is evaluated by Perceptual Evaluation of Speech Quality (PESQ) score and Signal to Noise Ratio (SNR) improvement for normal speech and Harmonic to Noise Ratio (HNR) for Oesophageal Speech (OES). Compared with previous systems, the normal speech indicates 30% increase in PESQ score, 4 dB SNR improvement and OES shows 3 dB HNR improvement.
An Optimal Algorithm for Linear Bandits
Cesa-Bianchi, Nicolò
2011-01-01
We provide the first algorithm for online bandit linear optimization whose regret after T rounds is of order sqrt{Td ln N} on any finite class X of N actions in d dimensions, and of order d*sqrt{T} (up to log factors) when X is infinite. These bounds are not improvable in general. The basic idea utilizes tools from convex geometry to construct what is essentially an optimal exploration basis. We also present an application to a model of linear bandits with expert advice. Interestingly, these results show that bandit linear optimization with expert advice in d dimensions is no more difficult (in terms of the achievable regret) than the online d-armed bandit problem with expert advice (where EXP4 is optimal).
Non-linear Kalman filters for calibration in radio interferometry
Tasse, Cyril
2014-01-01
We present a new calibration scheme based on a non-linear version of Kalman filter that aims at estimating the physical terms appearing in the Radio Interferometry Measurement Equation (RIME). We enrich the filter's structure with a tunable data representation model, together with an augmented measurement model for regularization. We show using simulations that it can properly estimate the physical effects appearing in the RIME. We found that this approach is particularly useful in the most extreme cases such as when ionospheric and clock effects are simultaneously present. Combined with the ability to provide prior knowledge on the expected structure of the physical instrumental effects (expected physical state and dynamics), we obtain a fairly cheap algorithm that we believe to be robust, especially in low signal-to-noise regime. Potentially the use of filters and other similar methods can represent an improvement for calibration in radio interferometry, under the condition that the effects corrupting visib...
Stochastic Optimal Estimation with Fuzzy Random Variables and Fuzzy Kalman Filtering
Institute of Scientific and Technical Information of China (English)
FENG Yu-hu
2005-01-01
By constructing a mean-square performance index in the case of fuzzy random variable, the optimal estimation theorem for unknown fuzzy state using the fuzzy observation data are given. The state and output of linear discrete-time dynamic fuzzy system with Gaussian noise are Gaussian fuzzy random variable sequences. An approach to fuzzy Kalman filtering is discussed. Fuzzy Kalman filtering contains two parts: a real-valued non-random recurrence equation and the standard Kalman filtering.
Local regularization of linear inverse problems via variational filtering
Lamm, Patricia K.
2017-08-01
We develop local regularization methods for ill-posed linear inverse problems governed by general Fredholm integral operators. The methods are executed as filtering algorithms which are simple to implement and computationally efficient for a large class of problems. We establish a convergence theory and give convergence rates for such methods, and illustrate their computational speed in numerical tests for inverse problems in geomagnetic exploration and imaging.
Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper shows how non-linear DSGE models with potential non-normal shocks can be estimated by Quasi-Maximum Likelihood based on the Central Difference Kalman Filter (CDKF). The advantage of this estimator is that evaluating the quasi log-likelihood function only takes a fraction of a second. T...
The optimal filtering of a class of dynamic multiscale systems
Institute of Scientific and Technical Information of China (English)
PAN Quan; ZHANG Lei; CUI Peiling; ZHANG Hongcai
2004-01-01
This paper discusses the optimal filtering of a class of dynamic multiscale systems (DMS), which are observed independently by several sensors distributed at different resolution spaces. The system is subject to known dynamic system model. The resolution and sampling frequencies of the sensors are supposed to decrease by a factor of two. By using the Haar wavelet transform to link the state nodes at each of the scales within a time block, a discrete-time model of this class of multiscale systems is given, and the conditions for applying Kalman filtering are proven. Based on the linear time-invariant system, the controllability and observability of the system and the stability of the Kalman filtering is studied, and a theorem is given. It is proved that the Kalman filter is stable if only the system is controllable and observable at the finest scale. Finally, a constant-velocity process is used to obtain insight into the efficiencies offered by our model and algorithm.
Optimal non-linear health insurance.
Blomqvist, A
1997-06-01
Most theoretical and empirical work on efficient health insurance has been based on models with linear insurance schedules (a constant co-insurance parameter). In this paper, dynamic optimization techniques are used to analyse the properties of optimal non-linear insurance schedules in a model similar to one originally considered by Spence and Zeckhauser (American Economic Review, 1971, 61, 380-387) and reminiscent of those that have been used in the literature on optimal income taxation. The results of a preliminary numerical example suggest that the welfare losses from the implicit subsidy to employer-financed health insurance under US tax law may be a good deal smaller than previously estimated using linear models.
Linear optimal control of tokamak fusion devices
Energy Technology Data Exchange (ETDEWEB)
Kessel, C.E.; Firestone, M.A.; Conn, R.W.
1989-05-01
The control of plasma position, shape and current in a tokamak fusion reactor is examined using linear optimal control. These advanced tokamaks are characterized by non up-down symmetric coils and structure, thick structure surrounding the plasma, eddy currents, shaped plasmas, superconducting coils, vertically unstable plasmas, and hybrid function coils providing ohmic heating, vertical field, radial field, and shaping field. Models of the electromagnetic environment in a tokamak are derived and used to construct control gains that are tested in nonlinear simulations with initial perturbations. The issues of applying linear optimal control to advanced tokamaks are addressed, including complex equilibrium control, choice of cost functional weights, the coil voltage limit, discrete control, and order reduction. Results indicate that the linear optimal control is a feasible technique for controlling advanced tokamaks where the more common classical control will be severely strained or will not work. 28 refs., 13 figs.
Filtering Non-Linear Transfer Functions on Surfaces.
Heitz, Eric; Nowrouzezahrai, Derek; Poulin, Pierre; Neyret, Fabrice
2014-07-01
Applying non-linear transfer functions and look-up tables to procedural functions (such as noise), surface attributes, or even surface geometry are common strategies used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient transfer function filtering remains an open problem for several reasons: transfer functions are complex and non-linear, especially when mapped through procedural noise and/or geometry-dependent functions, and the effects of perspective and masking further complicate the filtering over a pixel's footprint. We accurately solve this problem by computing and sampling from specialized filtering distributions on the fly, yielding very fast performance. We investigate the case where the transfer function to filter is a color map applied to (macroscale) surface textures (like noise), as well as color maps applied according to (microscale) geometric details. We introduce a novel representation of a (potentially modulated) color map's distribution over pixel footprints using Gaussian statistics and, in the more complex case of high-resolution color mapped microsurface details, our filtering is view- and light-dependent, and capable of correctly handling masking and occlusion effects. Our approach can be generalized to filter other physical-based rendering quantities. We propose an application to shading with irradiance environment maps over large terrains. Our framework is also compatible with the case of transfer functions used to warp surface geometry, as long as the transformations can be represented with Gaussian statistics, leading to proper view- and light-dependent filtering results. Our results match ground truth and our solution is well suited to real-time applications, requires only a few
OPTIMAL TARGET TRAJECTORY ESTIMATION AND FILTERING USING NETWORKED SENSORS
Institute of Scientific and Technical Information of China (English)
Jiangping HU; Xiaoming HU
2008-01-01
Target tracking using distributed sensor network is in general a challenging problem because it always needs to deal with real-time processing of noisy information. In this paper the problem of using nonlinear sensors such as distance and direction sensors for estimating a moving target is studied.The problem is formulated as a prudent design of nonlinear filters for a linear system subject to noisy nonlinear measurements and partially unknown input, which is generated by an exogenous system.In the worst case where the input is completely unknown, the exogenous dynamics is reduced to the random walk model. It can be shown that the nonlinear filter will have optimal convergence if the number of the sensors are large enough and the convergence rate will be highly improved if the sensors are deployed appropriately. This actually raises an interesting issue on active sensing: how to optimally move the sensors if they are considered as mobile multi-agent systems? Finally, a simulation example is given to illustrate and validate the construction of our filter.
Optimized object tracking technique using Kalman filter
Directory of Open Access Journals (Sweden)
Liana Ellen Taylor
2016-07-01
Full Text Available This paper focused on the design of an optimized object tracking technique which would minimize the processing time required in the object detection process while maintaining accuracy in detecting the desired moving object in a cluttered scene. A Kalman filter based cropped image is used for the image detection process as the processing time is significantly less to detect the object when a search window is used that is smaller than the entire video frame. This technique was tested with various sizes of the window in the cropping process. MATLAB® was used to design and test the proposed method. This paper found that using a cropped image with 2.16 multiplied by the largest dimension of the object resulted in significantly faster processing time while still providing a high success rate of detection and a detected center of the object that was reasonably close to the actual center.
Portfolio optimization using fuzzy linear programming
Pandit, Purnima K.
2013-09-01
Portfolio Optimization (PO) is a problem in Finance, in which investor tries to maximize return and minimize risk by carefully choosing different assets. Expected return and risk are the most important parameters with regard to optimal portfolios. In the simple form PO can be modeled as quadratic programming problem which can be put into equivalent linear form. PO problems with the fuzzy parameters can be solved as multi-objective fuzzy linear programming problem. In this paper we give the solution to such problems with an illustrative example.
A Novel Method of Edge Filter Linear Demodulation Using Long Period Grating in Fiber Sensor System
Institute of Scientific and Technical Information of China (English)
无
2003-01-01
A novel method of linear demodulation based on edge filter is presented. An experimental system is built up in which LPG is used as the edge filter. We achieve linear demodulation with a bandwidth of 5nm.
Topology Optimization - Improved Checker-Board Filtering With Sharp Contours
DEFF Research Database (Denmark)
Pedersen, Christian Gejl; Lund, Jeppe Jessen; Damkilde, Lars
2006-01-01
In topology optimization it is mandatory to use a filtering technique in order to prevent checker-boarder solutions. The paper examines a new filtering principle and demonstrates an improved sharpness in the contours. This was not realized in the original proposal of the filter. Furthermore...
An example in linear quadratic optimal control
Weiss, George; Zwart, Heiko J.
1998-01-01
We construct a simple example of a quadratic optimal control problem for an infinite-dimensional linear system based on a shift semigroup. This system has an unbounded control operator. The cost is quadratic in the input and the state, and the weighting operators are bounded. Despite its extreme
An example in linear quadratic optimal control
Weiss, George; Zwart, Heiko J.
1998-01-01
We construct a simple example of a quadratic optimal control problem for an infinite-dimensional linear system based on a shift semigroup. This system has an unbounded control operator. The cost is quadratic in the input and the state, and the weighting operators are bounded. Despite its extreme sim
A fault detection and isolation filter for discrete linear systems.
Giovanini, L; Dondo, R
2003-10-01
The problem of fault and/or abrupt disturbances detection and isolation for discrete linear systems is analyzed in this work. A strategy for detecting and isolating faults and/or abrupt disturbances is presented. The strategy is an extension of an already existing result in the continuous time domain to the discrete domain. The resulting detection algorithm is a Kalman filter with a special structure. The filter generates a residuals vector in such a way that each element of this vector is related with one fault or disturbance. Therefore the effects of the other faults, disturbances, and measurement noises in this element are minimized. The necessary stability and convergence conditions are briefly exposed. A numerical example is also presented.
Optimized multichannel decomposition for texture segmentation using Gabor filter bank
Nezamoddini-Kachouie, Nezamoddin; Alirezaie, Javad
2004-05-01
Texture segmentation and analysis is an important aspect of pattern recognition and digital image processing. Previous approaches to texture analysis and segmentation perform multi-channel filtering by applying a set of filters to the image. In this paper we describe a texture segmentation algorithm based on multi-channel filtering that is optimized using diagonal high frequency residual. Gabor band pass filters with different radial spatial frequencies and different orientations have optimum resolution in time and frequency domain. The image is decomposed by a set of Gabor filters into a number of filtered images; each one contains variation of intensity on a sub-band frequency and orientation. The features extracted by Gabor filters have been applied for image segmentation and analysis. There are some important considerations about filter parameters and filter bank coverage in frequency domain. This filter bank does not completely cover the corners of the frequency domain along the diagonals. In our method we optimize the spatial implementation for the Gabor filter bank considering the diagonal high frequency residual. Segmentation is accomplished by a feedforward backpropagation multi-layer perceptron that is trained by optimized extracted features. After MLP is trained the input image is segmented and each pixel is assigned to the proper class.
A Low Cost Structurally Optimized Design for Diverse Filter Types.
Kazmi, Majida; Aziz, Arshad; Akhtar, Pervez; Ikram, Nassar
2016-01-01
A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environment. Thus it calls for optimized solutions. Mostly the optimization of these filters are based on exploiting structural properties. A common shortcoming of all previously reported optimized approaches is their restricted applicability only for a specific filter type. These narrow scoped solutions completely disregard the versatility attribute of advanced image processing applications and in turn offset their effectiveness while implementing a complete application. This paper presents an efficient framework which exploits the structural properties of 2D-filters for effectually reducing its computational cost along with an added advantage of versatility for supporting diverse filter types. A composite symmetric filter structure is introduced which exploits the identities of quadrant and circular T-symmetries in two distinct filter regions simultaneously. These T-symmetries effectually reduce the number of filter coefficients and consequently its multipliers count. The proposed framework at the same time empowers this composite filter structure with additional capabilities of realizing all of its Ψ-symmetry based subtypes and also its special asymmetric filters case. The two-fold optimized framework thus reduces filter computational cost up to 75% as compared to the conventional approach as well as its versatility attribute not only supports diverse filter types but also offers further cost reduction via resource sharing for sequential implementation of diversified image
A hybrid method for optimization of the adaptive Goldstein filter
Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue
2014-12-01
The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.
Annular pupil filter under shot-noise condition for linear and non linear microscopy.
Ronzitti, Emiliano; Vicidomini, Giuseppe; Caorsi, Valentina; Diaspro, Alberto
2009-04-13
The imaging performances of multiphoton excitation and confocal laser scanning microscopy are herby considered: in typical experimental imaging conditions, a small finite amount of photon reaches the detector giving shot-noise fluctuations which affects the signal acquired. A significant detriment in the high frequencies transmission capability is obtained. In order to partially recover the high frequencies information lost, the insertion of a pupil plane filter in the microscope illumination light pathway on the objective lens is proposed. We demonstrate high-frequency and resolution enhancement in the case of linear and non linear fluorescence microscope approach under shot-noise condition.
Optimal filter bandwidth for pulse oximetry
Stuban, Norbert; Niwayama, Masatsugu
2012-10-01
Pulse oximeters contain one or more signal filtering stages between the photodiode and microcontroller. These filters are responsible for removing the noise while retaining the useful frequency components of the signal, thus improving the signal-to-noise ratio. The corner frequencies of these filters affect not only the noise level, but also the shape of the pulse signal. Narrow filter bandwidth effectively suppresses the noise; however, at the same time, it distorts the useful signal components by decreasing the harmonic content. In this paper, we investigated the influence of the filter bandwidth on the accuracy of pulse oximeters. We used a pulse oximeter tester device to produce stable, repetitive pulse waves with digitally adjustable R ratio and heart rate. We built a pulse oximeter and attached it to the tester device. The pulse oximeter digitized the current of its photodiode directly, without any analog signal conditioning. We varied the corner frequency of the low-pass filter in the pulse oximeter in the range of 0.66-15 Hz by software. For the tester device, the R ratio was set to R = 1.00, and the R ratio deviation measured by the pulse oximeter was monitored as a function of the corner frequency of the low-pass filter. The results revealed that lowering the corner frequency of the low-pass filter did not decrease the accuracy of the oxygen level measurements. The lowest possible value of the corner frequency of the low-pass filter is the fundamental frequency of the pulse signal. We concluded that the harmonics of the pulse signal do not contribute to the accuracy of pulse oximetry. The results achieved by the pulse oximeter tester were verified by human experiments, performed on five healthy subjects. The results of the human measurements confirmed that filtering out the harmonics of the pulse signal does not degrade the accuracy of pulse oximetry.
Arcasoy, C. C.
1992-11-01
The problem of multi-output, infinite-time, linear time-invariant optimal Kalman-Bucy filter both in continuous and discrete-time cases in frequency domain is addressed. A simple new algorithm is given for the analytical solution to the steady-state gain of the optimum filter based on a transfer function approach. The algorithm is based on spectral factorization of observed spectral density matrix of the filter which generates directly the return-difference matrix of the optimal filter. The method is more direct than by algebraic Riccati equation solution and can easily be implemented on digital computer. The design procedure is illustrated by examples and closed-form solution of ECV and ECA radar tracking filters are considered as an application of the method.
Practice Utilization of Algorithms for Analog Filter Group Delay Optimization
Directory of Open Access Journals (Sweden)
K. Hajek
2007-04-01
Full Text Available This contribution deals with an application of three different algorithms which optimize a group delay of analog filters. One of them is a part of the professional circuit simulator Micro Cap 7 and the others two original algorithms are developed in the MATLAB environment. An all-pass network is used to optimize the group delay of an arbitrary analog filter. Introduced algorithms look for an optimal order and optimal coefficients of an all-pass network transfer function. Theoretical foundations are introduced and all algorithms are tested using the optimization of testing analog filter. The optimization is always run three times because the second, third and fourth-order all-pass network is used. An equalization of the original group delay is a main objective of these optimizations. All outputs of all algorithms are critically evaluated and also described.
Construction of Two-Dimensional Compactly Supported Orthogonal Wavelets Filters with Linear Phase
Institute of Scientific and Technical Information of China (English)
Si Long PENG
2002-01-01
In this paper, a large class of two-dimensional orthogonal wavelet filters, (lowpass andhighpass), are presented in explicit expression. We also characterize the filters with linear phase in thiscase. Some examples are also given, including non-separable filters with linear phase.
Optimal Source-Based Filtering of Malicious Traffic
Soldo, Fabio; Markopoulou, Athina
2010-01-01
In this paper, we consider the problem of blocking malicious traffic on the Internet, via source-based filtering. In particular, we consider filtering via access control lists (ACLs): these are already available at the routers today but are a scarce resource because they are stored in the expensive ternary content addressable memory (TCAM). Aggregation (by filtering source prefixes instead of individual IP addresses) helps reduce the number of filters, but comes also at the cost of blocking legitimate traffic originating from the filtered prefixes. We show how to optimally choose which source prefixes to filter, for a variety of realistic attack scenarios and operators' policies. In each scenario, we design optimal, yet computationally efficient, algorithms. Using logs from Dshield.org, we evaluate the algorithms and demonstrate that they bring significant benefit in practice.
Optimal multihump filter for photometric redshifts
Budavari, Tamas; Szalay, Alexander S.; Csabai, Istvan; Connolly, Andrew J.; Tsvetanov, Zlatan
2001-01-01
We propose a novel type filter for multicolor imaging to improve on the photometric redshift estimation of galaxies. An extra filter - specific to a certain photometric system - may be utilized with high efficiency. We present a case study of the Hubble Space Telescope's Advanced Camera for Surveys and show that one extra exposure could cut down the mean square error on photometric redshifts by 34% over the z
Optimization-based particle filter for state and parameter estimation
Institute of Scientific and Technical Information of China (English)
Li Fu; Qi Fei; Shi Guangming; Zhang Li
2009-01-01
In recent years, the theory of particle filter has been developed and widely used for state and parameter estimation in nonlinear/non-Gaussian systems. Choosing good importance density is a critical issue in particle filter design. In order to improve the approximation of posterior distribution, this paper provides an optimization-based algorithm (the steepest descent method) to generate the proposal distribution and then sample particles from the distribution. This algorithm is applied in 1-D case, and the simulation results show that the proposed particle filter performs better than the extended Kalman filter (EKF), the standard particle filter (PF), the extended Kalman particle filter (PF-EKF) and the unscented particle filter (UPF) both in efficiency and in estimation precision.
Optimizing linear growth measurement in children.
Foote, Jan M
2014-01-01
A child's pattern of linear growth is one of the most sensitive indicators of health and well-being. However, many health care personnel use casual techniques and faulty instruments to measure children's growth and keep imprecise growth charts, making interpretation of growth patterns problematic. This situation can delay diagnosis and treatment of children with growth disorders and other conditions that affect growth. It can also lead to undue anxiety and unnecessary evaluation of children who are actually growing well. A clinical practice guideline was developed to optimize the accuracy and reliability of linear growth measurement. This article presents strategies to implement the guideline and thereby increase awareness of the importance of standardized growth measurement techniques and instruments, facilitate staff training and competency, and encourage standardized record keeping. These strategies will give providers more confidence in their interpretation of children's growth patterns and allow them to recognize potential problems, possibly before other symptoms appear.
Desensitized Optimal Filtering and Sensor Fusion Tool Kit Project
National Aeronautics and Space Administration — It is proposed to develop desensitized optimal filtering techniques and to implement these algorithms in a navigation and sensor fusion tool kit. These proposed...
Optimizing internal structure of membrane filters
Cummings, Linda; Sanaei, Pejman
2016-11-01
Membrane filters are in widespread use, and manufacturers have considerable interest in improving their performance, in terms of particle retention properties, and total throughput over the filter lifetime. In this regard, it has long been known that membrane properties should not be uniform over the membrane depth; rather, membrane permeability should decrease in the direction of flow. While much research effort has been focused on investigating favorable membrane permeability gradients, this work has been largely empirical in nature. We present a simple, first-principles model for flow through and fouling of a membrane filter, accounting for permeability gradients via variable pore size. Our model accounts for two fouling modes: sieving; and particle adsorption within pores. For filtration driven by a fixed pressure drop, flux through the membrane eventually goes to zero, as fouling occurs and pores close. We address issues of filter performance as the internal pore structure is varied, by comparing the total throughput obtained with equal-resistance membranes. Within certain classes of pore profiles we are able to find the optimum pore profile that maximizes total throughput over the filter lifetime, while maintaining acceptable particle removal from the feed. Partial support from NSF DMS 1261596 is gratefully acknowledged.
Directory of Open Access Journals (Sweden)
R. Caballero-Águila
2013-01-01
and each sensor noise are two-step cross-correlated. Under these assumptions and by an innovation approach, recursive algorithms for the optimal linear filter are derived by using the two basic estimation fusion structures; more specifically, both centralized and distributed fusion estimation algorithms are proposed. The accuracy of these estimators is measured by their error covariance matrices, which allow us to compare their performance in a numerical simulation example that illustrates the feasibility of the proposed filtering algorithms and shows a comparison with other existing filters.
Dynamic Optimization of Feedforward Automatic Gauge Control Based on Extended Kalman Filter
Institute of Scientific and Technical Information of China (English)
YANG Bin-hu; YANG Wei-dong; CHEN Lian-gui; QU Lei
2008-01-01
Automatic gauge control is an essentially nonlinear process varying with time delay, and stochastically varying input and process noise always influence the target gauge control accuracy. To improve the control capability of feedforward automatic gauge control, Kalman filter was employed to filter the noise signal transferred from one stand to another. The linearized matrix that the Kalman filter algorithm needed was concluded; thus, the feedforward automatic gauge control architecture was dynamically optimized. The theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.
H-infinity filtering for discrete-time switched linear systems under arbitrary switching
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
This paper is concerned with the problem of H-infinity filtering for discrete-time switched linear systems under arbitrary switching laws.New sufficient conditions for the solvability of the problem are given via switched quadratic Lyapunov functions.Based on Finsler's lemma,two sets of slack variables with special structure are introduced to provide extra degrees of freedom in optimizing the guaranteed H-infinity performance.Compared to the existing methods,the proposed one has better performances and less...
Image indexing and retrieval using linear phase coefficient composite filters
Carlotto, Mark J.
1996-01-01
Content-based retrieval techniques can be characterized in several ways: by the manner in which image data are indexed, by the level of specificity/generality of the query and response of the system, by the type of query (e.g., iconic or symbolic), and by the kind of information used (intrinsic image features or attached information such as text). The method described in this paper automatically indexes images in the database, and is intended to retrieve specific objects by image query based on inherent image content. Our method is actually quite similar to object recognition except that instead of searching a single image for a given object, an entire database of images is examined. The approach uses linear phase coefficient composite (LPCC) filters to encode and match queries consisting of multiple images (e.g., representative views of an object of interest) against multiple images in the database simultaneously. Retrieval is a two-step process that first isolates those portions of the database containing images that match the query, and then identifies the specific images. Our use of LPCC filters exploits phase information to retrieve specific images that match the query from the database. The results from the experiments suggest that phase information can be used to index and retrieve multiple images from a database in parallel, and that large numbers of operations can be performed simultaneously using a complex number representation. In one experiment well over 100 real correlations were effectively performed by a single complex correlation. Problems encountered in processing video data are discussed.
Sullivan, Shane Z.; Schmitt, Paul D.; DeWalt, Emma L.; Muir, Ryan D.; Simpson, Garth J.
2013-03-01
Photon counting represents the Poisson limit in signal to noise, but can often be complicated in imaging applications by detector paralysis, arising from the finite rise / fall time of the detector upon photon absorption. We present here an approach for reducing dead-time by generating a deconvolution digital filter based on optimizing the Fisher linear discriminant. In brief, two classes are defined, one in which a photon event is initiated at the origin of the digital filter, and one in the photon event is non-coincident with the filter origin. Linear discriminant analysis (LDA) is then performed to optimize the digital filter that best resolves the coincident and non-coincident training set data.1 Once trained, implementation of the filter can be performed quickly, significantly reducing dead-time issues and measurement bias in photon counting applications. Experimental demonstration of the LDA-filter approach was performed in fluorescence microscopy measurements using a highly convolved impulse response with considerable ringing. Analysis of the counts supports the capabilities of the filter in recovering deconvolved impulse responses under the conditions considered in the study. Potential additional applications and possible limitations are also considered.
Optimal Sharpening of Compensated Comb Decimation Filters: Analysis and Design
Directory of Open Access Journals (Sweden)
David Ernesto Troncoso Romero
2014-01-01
Full Text Available Comb filters are a class of low-complexity filters especially useful for multistage decimation processes. However, the magnitude response of comb filters presents a droop in the passband region and low stopband attenuation, which is undesirable in many applications. In this work, it is shown that, for stringent magnitude specifications, sharpening compensated comb filters requires a lower-degree sharpening polynomial compared to sharpening comb filters without compensation, resulting in a solution with lower computational complexity. Using a simple three-addition compensator and an optimization-based derivation of sharpening polynomials, we introduce an effective low-complexity filtering scheme. Design examples are presented in order to show the performance improvement in terms of passband distortion and selectivity compared to other methods based on the traditional Kaiser-Hamming sharpening and the Chebyshev sharpening techniques recently introduced in the literature.
The research of parallel-coupled linear-phase superconducting filter
Energy Technology Data Exchange (ETDEWEB)
Zhang, Tianliang; Zhou, Liguo; Yang, Kai, E-mail: kyang@uestc.edu.cn; Luo, Chao; Jiang, Mingyan; Dang, Wei; Ren, Xiangyang
2015-12-15
Highlights: • Parallel-connected linear phase filter can be achieved when the group delays of sub-networks compensate each other. • We give the coupling and routing diagrams of four linear phase filters with self-synthesized coupling matrixes, and verified the correctness of theory data and the feasibility of the circuit design. • There are a variety of topological coupling and routing diagrams for a same order filter. • We give a reasonable arrangement of design steps for high-order parallel-coupled linear phase filter. - Abstract: This paper presents a research on the mechanism of a linear phase filter constructed with parallel-connected sub-networks, considering that linear phase characteristic of a filter can be achieved when the group delays of sub-networks compensate each other. This paper also gives several coupling and routing diagrams of linear phase filters with different parallel-connected networks, and then the coupling matrixes of three 8-order filters and one 10-order filter are synthesized. One of the coupling matrixes is utilized to design a 8-order parallel-connected network high temperature superconducting (HTS) linear phase filter with two pairs of transmission zeros, so as to verify the correctness of theory data and the feasibility of the circuit design for the proposed 8-order and higher order parallel-connected network linear phase filter. The HTS linear phase filter is designed on YBCO/LaAlO{sub 3}/YBCO superconducting substrate, at 77 K, the measured center frequency is 2000 MHz with a bandwidth of 30 MHz, the insertion loss is less than 0.3 dB and the reflection is better than −12.5 dB in passband. The group delay is less than ±5 ns over the 60% passband, which shows that the filter has a good linear phase characteristic.
Optimal Filtering Algorithm for Stochastic 2-D FMM Ⅱ with Multiplicative Noise
Institute of Scientific and Technical Information of China (English)
CHU Dongsheng; LIANG Meng; SHI Xin; ZHANG Ling
2004-01-01
A stochastic two-dimensional Fornasini-Marchesini's Model Ⅱ (2-D FMM Ⅱ) with multiplicative noise is given,and a filtering algorithm for this model, which is optimal in the sense of linear minimum-variance, is developed. The stochastic 2-D FMM Ⅱ with multiplicative noise can be reduced to a 1-D model, and the proposed optimal filtering algorithm for the stochastic 2-D FMM Ⅱ with multiplicative noise is obtained by using the state estimation theory of 1-D systems. An example is given to illustrate the validity of this algorithm.
Linear systems optimal and robust control
Sinha, Alok
2007-01-01
Introduction Overview Contents of the Book State Space Description of a Linear System Transfer Function of a Single Input/Single Output (SISO) System State Space Realizations of a SISO System SISO Transfer Function from a State Space Realization Solution of State Space Equations Observability and Controllability of a SISO System Some Important Similarity Transformations Simultaneous Controllability and Observability Multiinput/Multioutput (MIMO) Systems State Space Realizations of a Transfer Function Matrix Controllability and Observability of a MIMO System Matrix-Fraction Description (MFD) MFD of a Transfer Function Matrix for the Minimal Order of a State Space Realization Controller Form Realization from a Right MFD Poles and Zeros of a MIMO Transfer Function Matrix Stability Analysis State Feedback Control and Optimization State Variable Feedback for a Single Input System Computation of State Feedback Gain Matrix for a Multiinput System State Feedback Gain Matrix for a Multi...
A linear feature space for simultaneous learning of spatio-spectral filters in BCI.
Farquhar, J
2009-11-01
It is shown how two of the most common types of feature mapping used for classification of single trial Electroencephalography (EEG), i.e. spatial and frequency filtering, can be equivalently performed as linear operations in the space of frequency-specific detector covariance tensors. Thus by first mapping the data to this space, a simple linear classifier can directly learn optimal spatial + frequency filters. Significantly, if the classifier's loss function is convex, learning these filters is a convex minimisation problem. It is also shown how to pre-process the data such that the resulting decision function is robust to the biases inherent in EEG data. Further, based upon ideas from Max Margin Matrix Factorisation, it is shown how the trace norm can be used to select solutions which have low rank. Low rank solutions are preferred as they reflect prior information about the types of EEG signals we expect to see, i.e. that the classifiable information is contained in only a few spatio/spectral pairs. They are also easier to interpret. This feature-space transformation is compared with the Common-Spatial-Patterns on simulated and real Imagined Movement Brain Computer Interface (BCI) data and shown to give state-of-the-art performance.
Design of Reversible Multipliers for Linear Filtering Applications in DSP
Directory of Open Access Journals (Sweden)
Rakshith Saligram
2012-12-01
Full Text Available Multipliers in DSP computations are crucial. Thus modern DSP systems need to develop low power multipliers to reduce the power dissipation. One of the efficient ways to reduce power dissipation is by the use of bypassing technique. If a bit in the multiplier and/or multiplicand is zero the whole array of rowand/or diagonal will be bypassed and hence the name bypass multipliers. This paper presents the column Bypass multiplier and 2-D bypass multiplier using reversible logic; Reversible logic is a more prominent technology, having its applications in Low Power CMOS and quantum computations. The switching activity of any component in the bypass multiplier depends only on the input bit coefficients. The semultipliers find application in linear filtering FFT computational units, particularly during zero padding where there will be umpteen numbers of zeros. A bypass multiplier reduces the number of switching activities as well as the power consumption, above which reversible logic design acts to further almost nullify the dissipations
Fast Kalman-like filtering for large-dimensional linear and Gaussian state-space models
Ait-El-Fquih, Boujemaa
2015-08-13
This paper considers the filtering problem for linear and Gaussian state-space models with large dimensions, a setup in which the optimal Kalman Filter (KF) might not be applicable owing to the excessive cost of manipulating huge covariance matrices. Among the most popular alternatives that enable cheaper and reasonable computation is the Ensemble KF (EnKF), a Monte Carlo-based approximation. In this paper, we consider a class of a posteriori distributions with diagonal covariance matrices and propose fast approximate deterministic-based algorithms based on the Variational Bayesian (VB) approach. More specifically, we derive two iterative KF-like algorithms that differ in the way they operate between two successive filtering estimates; one involves a smoothing estimate and the other involves a prediction estimate. Despite its iterative nature, the prediction-based algorithm provides a computational cost that is, on the one hand, independent of the number of iterations in the limit of very large state dimensions, and on the other hand, always much smaller than the cost of the EnKF. The cost of the smoothing-based algorithm depends on the number of iterations that may, in some situations, make this algorithm slower than the EnKF. The performances of the proposed filters are studied and compared to those of the KF and EnKF through a numerical example.
Adaptive Linear Filtering Design with Minimum Symbol Error Probability Criterion
Institute of Scientific and Technical Information of China (English)
Sheng Chen
2006-01-01
Adaptive digital filtering has traditionally been developed based on the minimum mean square error (MMSE)criterion and has found ever-increasing applications in communications. This paper presents an alternative adaptive filtering design based on the minimum symbol error rate (MSER) criterion for communication applications. It is shown that the MSER filtering is smarter, as it exploits the non-Gaussian distribution of filter output effectively. Consequently, it provides significant performance gain in terms of smaller symbol error over the MMSE approach. Adopting Parzen window or kernel density estimation for a probability density function, a block-data gradient adaptive MSER algorithm is derived. A stochastic gradient adaptive MSER algorithm, referred to as the least symbol error rate, is further developed for sampleby-sample adaptive implementation of the MSER filtering. Two applications, involving single-user channel equalization and beamforming assisted receiver, are included to demonstrate the effectiveness and generality of the proposed adaptive MSER filtering approach.
Optimal Filtering in Pilot-Aided Carrier Recovery
Directory of Open Access Journals (Sweden)
Arnaldo Spalvieri
2009-01-01
Full Text Available The paper deals with carrier recovery based on pilot symbols in single-carrier systems. Wiener's method is used to determine the optimal unconstrained filter in estimation of phase noise assuming that a sequence of equally spaced pilot symbols is available. Our analysis allows to capture two effects that are not considered in the existing literature: the impact of aliasing due to sampling of the phase noise sequence at the pilot rate and the cyclostationary nature of the estimate hence of its performance. Experimental results are derived also for the case, where the filter is constrained to the cascade of two moving averages. These results show that, in the considered example, the mean-square phase error of the constrained filter is within 0.35 dB from the MSE of the optimal filter.
The research of parallel-coupled linear-phase superconducting filter
Zhang, Tianliang; Zhou, Liguo; Yang, Kai; Luo, Chao; Jiang, Mingyan; Dang, Wei; Ren, Xiangyang
2015-12-01
This paper presents a research on the mechanism of a linear phase filter constructed with parallel-connected sub-networks, considering that linear phase characteristic of a filter can be achieved when the group delays of sub-networks compensate each other. This paper also gives several coupling and routing diagrams of linear phase filters with different parallel-connected networks, and then the coupling matrixes of three 8-order filters and one 10-order filter are synthesized. One of the coupling matrixes is utilized to design a 8-order parallel-connected network high temperature superconducting (HTS) linear phase filter with two pairs of transmission zeros, so as to verify the correctness of theory data and the feasibility of the circuit design for the proposed 8-order and higher order parallel-connected network linear phase filter. The HTS linear phase filter is designed on YBCO/LaAlO3/YBCO superconducting substrate, at 77 K, the measured center frequency is 2000 MHz with a bandwidth of 30 MHz, the insertion loss is less than 0.3 dB and the reflection is better than -12.5 dB in passband. The group delay is less than ±5 ns over the 60% passband, which shows that the filter has a good linear phase characteristic.
IMAGE RESTORATION: DESIGN OF NON-LINEAR FILTER (LR
Directory of Open Access Journals (Sweden)
Shenbagarajan Anantharajan
2012-11-01
Full Text Available In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.
Performance analysis of Non Linear Filtering Algorithms for underwater images
Padmavathi, Dr G; Kumar, Mr M Muthu; Thakur, Suresh Kumar
2009-01-01
Image filtering algorithms are applied on images to remove the different types of noise that are either present in the image during capturing or injected in to the image during transmission. Underwater images when captured usually have Gaussian noise, speckle noise and salt and pepper noise. In this work, five different image filtering algorithms are compared for the three different noise types. The performances of the filters are compared using the Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). The modified spatial median filter gives desirable results in terms of the above two parameters for the three different noise. Forty underwater images are taken for study.
A boosted optimal linear learner for retinal vessel segmentation
Poletti, E.; Grisan, E.
2014-03-01
Ocular fundus images provide important information about retinal degeneration, which may be related to acute pathologies or to early signs of systemic diseases. An automatic and quantitative assessment of vessel morphological features, such as diameters and tortuosity, can improve clinical diagnosis and evaluation of retinopathy. At variance with available methods, we propose a data-driven approach, in which the system learns a set of optimal discriminative convolution kernels (linear learner). The set is progressively built based on an ADA-boost sample weighting scheme, providing seamless integration between linear learner estimation and classification. In order to capture the vessel appearance changes at different scales, the kernels are estimated on a pyramidal decomposition of the training samples. The set is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). We tested the approach fundus images available from the DRIVE dataset. We show that the segmentation performance yields an accuracy of 0.94.
Robust output feedback H-infinity control and filtering for uncertain linear systems
Chang, Xiao-Heng
2014-01-01
"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.
Design and performance optimization of fiber optic adaptive filters.
Paparao, P; Ghosh, A; Allen, S D
1991-05-10
There is a great need for easy-to-fabricate and versatile fiber optic signal processing systems in which optical fibers are used for the delay and storage of wideband guided lightwave signals. We describe the design of the least-mean-square algorithm-based fiber optic adaptive filters for processing guided lightwave signals in real time. Fiber optic adaptive filters can learn to change their parameters or to process a set of characteristics of the input signal. In our realization we employ as few electronic devices as possible and use optical computation to utilize the advantages of optics in the processing speed, parallelism, and interconnection. Many schemes for optical adaptive filtering of electronic signals are available in the literature. The new optical adaptive filters described in this paper are for optical processing of guided lightwave signals, not electronic signals. We analyzed the convergence or learning characteristics of the adaptive filtering process as a function of the filter parameters and the fiber optic hardware errors. From this analysis we found that the effects of the optical round-off errors and noise can be reduced, and the learning speed can be comparatively increased in our design through an optimal selection of the filter parameters. A general knowledge of the fiber optic hardware, the statistics of the lightwave signal, and the desired goal of the adaptive processing are enough for this optimum selection of the parameters. Detailed computer simulations validate the theoretical results of performance optimization.
Directory of Open Access Journals (Sweden)
I. Sharma
2016-09-01
Full Text Available In this paper, a linear phase FIR filter is designed through recently proposed nature inspired optimization algorithm known as Cuckoo search (CS. A comparative study of Cuckoo search (CS, particle swarm optimization (PSO and artificial bee colony (ABC nature inspired optimization methods in the field of linear phase FIR filter design is also presented. For this purpose, an improved L1 weighted error function is formulated in frequency domain, and minimized through CS, PSO and ABC respectively. The error or objective function has a controlling parameter wt which controls the amount of ripple in the desired band of frequency. The performance of FIR filter is examined through three key parameters; Maximum Pass Band Ripple (MPR, Maximum Stopband Ripple (MSR and Stopband Attenuation (As. Comparative study and the simulation results reveal that the designed filter with CS gives better performance in terms of Maximum Stopband Ripple (MSR, and Stopband Attenuation (As for low order filter design, and for higher order it also gives better performance in term of Maximum Passband Ripple (MPR. Superiority of the proposed technique is also shown through comparison with other recently proposed methods.
Investigation of a possible process identity between DRM and Linear Filtering
1997-01-01
The classical analogy between linear filtering and acoustical filtering by tubes is applied in the non-classical case where the tubes are made of unequal-length sections (such as the DRM case). It is shown that the filtering process identity is substantially more complicated than in the case of equal-length sections. In particular, it prevents the use of the Levinson algorithm for inverting the filtering process and recovering the tube characteristics from sound alone.
Combinatorial optimization tolerances calculated in linear time
Goldengorin, Boris; Sierksma, Gerard
2003-01-01
For a given optimal solution to a combinatorial optimization problem, we show, under very natural conditions, the equality of the minimal values of upper and lower tolerances, where the upper tolerances are calculated for the given optimal solution and the lower tolerances outside the optimal
Combinatorial optimization tolerances calculated in linear time
Goldengorin, Boris; Sierksma, Gerard
2003-01-01
For a given optimal solution to a combinatorial optimization problem, we show, under very natural conditions, the equality of the minimal values of upper and lower tolerances, where the upper tolerances are calculated for the given optimal solution and the lower tolerances outside the optimal soluti
Non-linear DSGE Models, The Central Difference Kalman Filter, and The Mean Shifted Particle Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
. The second contribution of this paper is to derive a new particle filter which we term the Mean Shifted Particle Filter (MSPFb). We show that the MSPFb outperforms the standard Particle Filter by delivering more precise state estimates, and in general the MSPFb has lower Monte Carlo variation in the reported...
Fuel cell cathode air filters: Methodologies for design and optimization
Kennedy, Daniel M.; Cahela, Donald R.; Zhu, Wenhua H.; Westrom, Kenneth C.; Nelms, R. Mark; Tatarchuk, Bruce J.
Proton exchange membrane (PEM) fuel cells experience performance degradation, such as reduction in efficiency and life, as a result of poisoning of platinum catalysts by airborne contaminants. Research on these contaminant effects suggests that the best possible solution to allowing fuel cells to operate in contaminated environments is by filtration of the harmful contaminants from the cathode air. A cathode air filter design methodology was created that connects properties of cathode air stream, filter design options, and filter footprint, to a set of adsorptive filter parameters that must be optimized to efficiently operate the fuel cell. Filter optimization requires a study of the trade off between two causal factors of power loss: first, a reduction in power production due to poisoning of the platinum catalyst by chemical contaminants and second, an increase in power requirements to operate the air compressor with a larger pressure drop from additional contaminant filtration. The design methodology was successfully applied to a 1.2 kW fuel cell using a programmable algorithm and predictions were made about the relationships between inlet concentration, breakthrough time, filter design, pressure drop, and compressor power requirements.
Optimized digital filtering techniques for radiation detection with HPGe detectors
Salathe, M
2015-01-01
This paper describes state-of-the-art digital filtering techniques that are part of the tool kit GEANA which is used as a fast automatic data validation tool for the GERDA experiment. The discussed filters include a novel, nonlinear correction method for ballistic deficits, which is combined with one of three shaping filters: the pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The performance of the filters is demonstrated using a 762 g high purity germanium detector that measures gamma-ray lines from radioactive sources in an energy range between 59 and 2615 keV. The modified cusp filter was found to be most optimal for individual gamma-ray lines. Furthermore, it was observed, that even though, the shaping time that minimizes the energy resolution is energy dependent, the loss in resolution by using a constant shaping time over the entire energy range is small, i.e. less than 32 eV for the pseudo-Gaussian filter. This together with good energy resolutions, e.g. 1.59 keV at 1333 keV, this ...
Linear polymer separation using carbon-nanotube-modified centrifugal filter units.
Krawczyk, Tomasz; Marian, Karolina; Pawlyta, Mirosława
2016-02-01
The separation of linear polymers such as polysaccharides and polyethylene glycol was performed with modified commercial centrifugal filter units. The deposition of a 0.16-0.35 μm layer of modified carbon nanotubes prevented permeation of linear polymers of molecular weight higher than 20 000 Da through the membrane. It allowed facile purification of solution of 0.1 g of polymer samples from small molecules within 25 min by using a bench-top centrifuge. The structure of modified carbon nanotubes was optimized in order to achieve good adhesion to the low binding regenerated cellulose surface and low solubility in aqueous solutions after deposition. The best modification of carbon nanotubes was oxidation and subsequent amide formation of diethanolamine. Introduction of acetic acid groups using sodium chloroacetate worked equally well. The modified filter could be used multiple times without the decrease of the efficiency. The carbon nanotubes layer was stable in aqueous solutions in a pH range of 1-7. The proposed method provides a convenient way of purification of modified polymers in research areas such as drug delivery or macromolecular probes synthesis.
Optimal filtering in multipulse sequences for nuclear quadrupole resonance detection
Osokin, D. Ya.; Khusnutdinov, R. R.; Mozzhukhin, G. V.; Rameev, B. Z.
2014-05-01
The application of the multipulse sequences in nuclear quadrupole resonance (NQR) detection of explosive and narcotic substances has been studied. Various approaches to increase the signal to noise ratio (SNR) of signal detection are considered. We discussed two modifications of the phase-alternated multiple-pulse sequence (PAMS): the 180° pulse sequence with a preparatory pulse and the 90° pulse sequence. The advantages of optimal filtering to detect NQR in the case of the coherent steady-state precession have been analyzed. It has been shown that this technique is effective in filtering high-frequency and low-frequency noise and increasing the reliability of NQR detection. Our analysis also shows the PAMS with 180° pulses is more effective than PSL sequence from point of view of the application of optimal filtering procedure to the steady-state NQR signal.
An Ant Colony Optimization Algorithm for Microwave Corrugated Filters Design
Directory of Open Access Journals (Sweden)
Ivan A. Mantilla-Gaviria
2013-01-01
Full Text Available A practical and useful application of the Ant Colony Optimization (ACO method for microwave corrugated filter design is shown. The classical, general purpose ACO method is adapted to deal with the microwave filter design problem. The design strategy used in this paper is an iterative procedure based on the use of an optimization method along with an electromagnetic simulator. The designs of high-pass and band-pass microwave rectangular waveguide filters working in the C-band and X-band, respectively, for communication applications, are shown. The average convergence performance of the ACO method is characterized by means of Monte Carlo simulations and compared with that obtained with the well-known Genetic Algorithm (GA. The overall performance, for the simulations presented herein, of the ACO is found to be better than that of the GA.
Joint state and parameter estimation in particle filtering and stochastic optimization
Institute of Scientific and Technical Information of China (English)
Xiaojun YANG; Keyi XING; Kunlin SHI; Quan PAN
2008-01-01
In this paper,an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approximation(SPSA)technique.The estimations of parameters are obtained by maximum-likelihood estimation and sampling within particle filtering framework,and the SPSA is used for stochastic optimization and to approximate the gradient of the cost function.The proposed algorithm achieves combined estimation of dynamic state and static parameters of nonlinear systerns.Simulation result demonstrates the feasibility and efficiency of the proposed algorithm.
Optimal Linear Joint Source-Channel Coding with Delay Constraint
Johannesson, Erik; Bernhardsson, Bo; Ghulchak, Andrey
2012-01-01
The problem of joint source-channel coding is considered for a stationary remote (noisy) Gaussian source and a Gaussian channel. The encoder and decoder are assumed to be causal and their combined operations are subject to a delay constraint. It is shown that, under the mean-square error distortion metric, an optimal encoder-decoder pair from the linear and time-invariant (LTI) class can be found by minimization of a convex functional and a spectral factorization. The functional to be minimized is the sum of the well-known cost in a corresponding Wiener filter problem and a new term, which is induced by the channel noise and whose coefficient is the inverse of the channel's signal-to-noise ratio. This result is shown to also hold in the case of vector-valued signals, assuming parallel additive white Gaussian noise channels. It is also shown that optimal LTI encoders and decoders generally require infinite memory, which implies that approximations are necessary. A numerical example is provided, which compares ...
Directory of Open Access Journals (Sweden)
Apoorva Aggarwal
2015-12-01
Full Text Available In this paper, an optimal design of linear phase digital finite impulse response (FIR highpass (HP filter using the L1-norm based real-coded genetic algorithm (RCGA is investigated. A novel fitness function based on L1 norm is adopted to enhance the design accuracy. Optimized filter coefficients are obtained by defining the filter objective function in L1 sense using RCGA. Simulation analysis unveils that the performance of the RCGA adopting this fitness function is better in terms of signal attenuation ability of the filter, flatter passband and the convergence rate. Observations are made on the percentage improvement of this algorithm over the gradient-based L1 optimization approach on various factors by a large amount. It is concluded that RCGA leads to the best solution under specified parameters for the FIR filter design on account of slight unnoticeable higher transition width.
Generation of Long Waves using Non-Linear Digital Filters
DEFF Research Database (Denmark)
Høgedal, Michael; Frigaard, Peter; Christensen, Morten
1994-01-01
transform of the 1st order surface elevation and subsequently inverse Fourier transformed. Hence, the methods are unsuitable for real-time applications, for example where white noise are filtered digitally to obtain a wave spectrum with built-in stochastic variabillity. In the present paper an approximative...... method for including the correct 2nd order bound terms in such applications is presented. The technique utilizes non-liner digital filters fitted to the appropriate transfer function is derived only for bounded 2nd order subharmonics, as they laboratory experiments generally are considered the most...
Institute of Scientific and Technical Information of China (English)
LI; Zicheng; SUN; Yukun
2006-01-01
Considering the detection principle that "when load current is periodic current, the integral in a cycle for absolute value of load current subtracting fundamental active current is the least", harmonic current real-time detection methods for power active filter are proposed based on direct computation, simple iterative algorithm and optimal iterative algorithm. According to the direct computation method, the amplitude of the fundamental active current can be accurately calculated when load current is placed in stable state. The simple iterative algorithm and the optimal iterative algorithm provide an idea about judging the state of load current. On the basis of the direct computation method, the simple iterative algorithm, the optimal iterative algorithm and precise definition of the basic concepts such as the true amplitude of the fundamental active current when load current is placed in varying state, etc., the double linear construction idea is proposed in which the amplitude of the fundamental active current at the moment of the sample is accurately calculated by using the first linear construction and the condition which disposes the next sample is created by using the second linear construction. On the basis of the double linear construction idea, a harmonic current real-time detection method for power active filter is proposed based on the double linear construction algorithm. This method has the characteristics of small computing quantity, fine real-time performance, being capable of accurately calculating the amplitude of the fundamental active current and so on.
OPTIMAL WAVELET FILTER DESIGN FOR REMOTE SENSING IMAGE COMPRESSION
Institute of Scientific and Technical Information of China (English)
Yang Guoan; Zheng Nanning; Guo Shugang
2007-01-01
A new approach for designing the Biorthogonal Wavelet Filter Bank (BWFB) for the purpose of image compression is presented in this letter. The approach is decomposed into two steps.First, an optimal filter bank is designed in theoretical sense based on Vaidyanathan's coding gain criterion in SubBand Coding (SBC) system. Then the above filter bank is optimized based on the criterion of Peak Signal-to-Noise Ratio (PSNR) in JPEG2000 image compression system, resulting in a BWFB in practical application sense. With the approach, a series of BWFB for a specific class of applications related to image compression, such as remote sensing images, can be fast designed. Here,new 5/3 BWFB and 9/7 BWFB are presented based on the above approach for the remote sensing image compression applications. Experiments show that the two filter banks are equally performed with respect to CDF 9/7 and LT 5/3 filter in JPEG2000 standard; at the same time, the coefficients and the lifting parameters of the lifting scheme are all rational, which bring the computational advantage, and the ease for VLSI implementation.
Optimization of Dynamic Range of Cascade Filter Realization
Directory of Open Access Journals (Sweden)
J. Hospodka
2006-09-01
Full Text Available This paper deals with a dynamic range optimization procedure for active filters based on the cascade realization. Dynamic characteristics of the cascade filter depend on many factors, mainly on pole-zero pairing, section ordering and gain assignment. Just the procedure for an optimal gain assignment for particular biquadratic sections is discussed in this paper. The input parameters of the procedure are parameters of particular biquads i.e. pole frequency ÃÂ‰0, quality factor Q, eventually zero frequency ÃÂ‰n for elliptic section and the transfer function type of the section. The gain is distributed so that output signal limitation of particular biquads occurs for the same level of the filter input signal. The procedure is versatile - can be used for analog as well as for digital filters with the cascade structure. The presented algorithm is fully universal (does not suppose any simplification. It has been used in Syntfil package for the filter design in the mathematical program Maple.
Weighted Ensemble Square Root Filters for Non-linear, Non-Gaussian, Data Assimilation
Livings, D. M.; van Leeuwen, P.
2012-12-01
In recent years the Ensemble Kalman Filter (EnKF) has become widely-used in both operational and research data assimilation systems. The particle filter is an alternative ensemble-based algorithm that offers the possibility of improved performance in non-linear and non-Gaussian problems. Papadakis et al (2010) introduced the Weighted Ensemble Kalman Filter (WEnKF) as a combination of the best features of the EnKF and the particle filter. Published work on the WEnKF has so far concentrated on the formulation of the EnKF in which observations are perturbed; no satisfactory general framework has been given for particle filters based on the alternative formulation of the EnKF known as the ensemble square root filter. This presentation will provide such a framework and show how several popular ensemble square root filters fit into it. No linear or Gaussian assumptions about the dynamical or observational models will be necessary. By examining the algorithms closely, shortcuts will be identified that increase both the simplicity and the efficiency of the resulting particle filter in comparison with a naive implementation. A procedure will be given for simply converting an existing ensemble square root filter into a particle filter. The procedure will not be limited to basic ensemble square root filters, but will be able to incorporate common variations such as covariance inflation without making any approximations.
Optimized Paraunitary Filter Banks for Time-Frequency Channel Diagonalization
Directory of Open Access Journals (Sweden)
Ju Ziyang
2010-01-01
Full Text Available We adopt the concept of channel diagonalization to time-frequency signal expansions obtained by DFT filter banks. As a generalization of the frequency domain channel representation used by conventional orthogonal frequency-division multiplexing receivers, the time-frequency domain channel diagonalization can be applied to time-variant channels and aperiodic signals. An inherent error in the case of doubly dispersive channels can be limited by choosing adequate windows underlying the filter banks. We derive a formula for the mean-squared sample error in the case of wide-sense stationary uncorrelated scattering (WSSUS channels, which serves as objective function in the window optimization. Furthermore, an enhanced scheme for the parameterization of tight Gabor frames enables us to constrain the window in order to define paraunitary filter banks. We show that the design of windows optimized for WSSUS channels with known statistical properties can be formulated as a convex optimization problem. The performance of the resulting windows is investigated under different channel conditions, for different oversampling factors, and compared against the performance of alternative windows. Finally, a generic matched filter receiver incorporating the proposed channel diagonalization is discussed which may be essential for future reconfigurable radio systems.
Optimized Paraunitary Filter Banks for Time-Frequency Channel Diagonalization
Ju, Ziyang; Hunziker, Thomas; Dahlhaus, Dirk
2010-12-01
We adopt the concept of channel diagonalization to time-frequency signal expansions obtained by DFT filter banks. As a generalization of the frequency domain channel representation used by conventional orthogonal frequency-division multiplexing receivers, the time-frequency domain channel diagonalization can be applied to time-variant channels and aperiodic signals. An inherent error in the case of doubly dispersive channels can be limited by choosing adequate windows underlying the filter banks. We derive a formula for the mean-squared sample error in the case of wide-sense stationary uncorrelated scattering (WSSUS) channels, which serves as objective function in the window optimization. Furthermore, an enhanced scheme for the parameterization of tight Gabor frames enables us to constrain the window in order to define paraunitary filter banks. We show that the design of windows optimized for WSSUS channels with known statistical properties can be formulated as a convex optimization problem. The performance of the resulting windows is investigated under different channel conditions, for different oversampling factors, and compared against the performance of alternative windows. Finally, a generic matched filter receiver incorporating the proposed channel diagonalization is discussed which may be essential for future reconfigurable radio systems.
Directory of Open Access Journals (Sweden)
Samuel Boudet
2014-01-01
Full Text Available Muscle artifacts constitute one of the major problems in electroencephalogram (EEG examinations, particularly for the diagnosis of epilepsy, where pathological rhythms occur within the same frequency bands as those of artifacts. This paper proposes to use the method dual adaptive filtering by optimal projection (DAFOP to automatically remove artifacts while preserving true cerebral signals. DAFOP is a two-step method. The first step consists in applying the common spatial pattern (CSP method to two frequency windows to identify the slowest components which will be considered as cerebral sources. The two frequency windows are defined by optimizing convolutional filters. The second step consists in using a regression method to reconstruct the signal independently within various frequency windows. This method was evaluated by two neurologists on a selection of 114 pages with muscle artifacts, from 20 clinical recordings of awake and sleeping adults, subject to pathological signals and epileptic seizures. A blind comparison was then conducted with the canonical correlation analysis (CCA method and conventional low-pass filtering at 30 Hz. The filtering rate was 84.3% for muscle artifacts with a 6.4% reduction of cerebral signals even for the fastest waves. DAFOP was found to be significantly more efficient than CCA and 30 Hz filters. The DAFOP method is fast and automatic and can be easily used in clinical EEG recordings.
LLSURE: local linear SURE-based edge-preserving image filtering.
Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin
2013-01-01
In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.
Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem
Rahmalia, Dinita
2017-08-01
Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.
Design and Efficiency Analysis of one Class of Uniform Linear Phase FIR Filter Banks
Directory of Open Access Journals (Sweden)
R. D. Pantić
2013-11-01
Full Text Available One class of uniform linear phase filter banks with different numbers of band-pass channels will be considered in this study, concentrating on 5, 9 and 17-band filter banks and their mutual comparison concerning delay and implementation complexity. Designed banks are based on the FIR filters and frequency response masking technique and are also compared to the banks with direct realization considering complementarity and delay.
[Optimizing algorithm design of piecewise linear classifier for spectra].
Lan, Tian-Ge; Fang, Yong-Hua; Xiong, Wei; Kong, Chao; Li, Da-Cheng; Dong, Da-Ming
2008-11-01
Being able to identify pollutant gases quickly and accurately is a basic request of spectroscopic technique for envirment monitoring for spectral classifier. Piecewise linear classifier is simple needs less computational time and approachs nonlinear boundary beautifully. Combining piecewise linear classifier and linear support vector machine which is based on the principle of maximizing margin, an optimizing algorithm for single side piecewise linear classifier was devised. Experimental results indicate that the piecewise linear classifier trained by the optimizing algorithm proposed in this paper can approach nonolinear boundary with fewer super_planes and has higher veracity for classification and recognition.
A Riccati approach for constrained linear quadratic optimal control
Sideris, Athanasios; Rodriguez, Luis A.
2011-02-01
An active-set method is proposed for solving linear quadratic optimal control problems subject to general linear inequality path constraints including mixed state-control and state-only constraints. A Riccati-based approach is developed for efficiently solving the equality constrained optimal control subproblems generated during the procedure. The solution of each subproblem requires computations that scale linearly with the horizon length. The algorithm is illustrated with numerical examples.
The optimal encodings for biased association in linear associative memories.
Leung, Yee; Dong, Tian Xin; Xu, Zong Ben
1998-07-01
In this paper, optimal encoding schemes for linear associative memories are derived for biased association under both the white-noise and colored-noise situations. Analysis and simulation results all show that the biased encodings thus derived are optimal and superior to existing models in their performance. Together with the Wee-Kohonen unbiased encoding, the study settles the optimality issue of linear associative memories and enhances their practicalities.
Numerical methods for control optimization in linear systems
Tyatyushkin, A. I.
2015-05-01
Numerical methods are considered for solving optimal control problems in linear systems, namely, terminal control problems with control and phase constraints and time-optimal control problems. Several algorithms with various computer storage requirements are proposed for solving these problems. The algorithms are intended for finding an optimal control in linear systems having certain features, for example, when the reachable set of a system has flat faces.
Optimal impulse control problems and linear programming.
Bauso, D.
2009-01-01
Optimal impulse control problems are, in general, difficult to solve. A current research goal is to isolate those problems that lead to tractable solutions. In this paper, we identify a special class of optimal impulse control problems which are easy to solve. Easy to solve means that solution algorithms are polynomial in time and therefore suitable to the on-line implementation in real-time problems. We do this by using a paradigm borrowed from the Operations Research field. As main result, ...
A neural network-based optimal spatial filter design method for motor imagery classification.
Directory of Open Access Journals (Sweden)
Ayhan Yuksel
Full Text Available In this study, a novel spatial filter design method is introduced. Spatial filtering is an important processing step for feature extraction in motor imagery-based brain-computer interfaces. This paper introduces a new motor imagery signal classification method combined with spatial filter optimization. We simultaneously train the spatial filter and the classifier using a neural network approach. The proposed spatial filter network (SFN is composed of two layers: a spatial filtering layer and a classifier layer. These two layers are linked to each other with non-linear mapping functions. The proposed method addresses two shortcomings of the common spatial patterns (CSP algorithm. First, CSP aims to maximize the between-classes variance while ignoring the minimization of within-classes variances. Consequently, the features obtained using the CSP method may have large within-classes variances. Second, the maximizing optimization function of CSP increases the classification accuracy indirectly because an independent classifier is used after the CSP method. With SFN, we aimed to maximize the between-classes variance while minimizing within-classes variances and simultaneously optimizing the spatial filter and the classifier. To classify motor imagery EEG signals, we modified the well-known feed-forward structure and derived forward and backward equations that correspond to the proposed structure. We tested our algorithm on simple toy data. Then, we compared the SFN with conventional CSP and its multi-class version, called one-versus-rest CSP, on two data sets from BCI competition III. The evaluation results demonstrate that SFN is a good alternative for classifying motor imagery EEG signals with increased classification accuracy.
McDonald, Alison C; Sanei, Kia; Keir, Peter J
2013-06-01
Muscle force estimates are important for full understanding of the musculoskeletal system and EMG is a modeling method used to estimate muscle force. The purpose of this investigation was to examine the effect of high pass filtering and non-linear normalization on the EMG-force relationship of sub-maximal finger exertions. Sub-maximal isometric ramp exertions were performed under three conditions (i) extension with restraint at the mid-proximal phalanx, (ii) flexion at the proximal phalanx and (iii) flexion at the distal phalanx. Thirty high pass filter designs were compared to a standardized processing procedure and an exponential fit equation was used for non-linear normalization. High pass filtering significantly reduced the %RMS error and increased the peak cross correlation between EMG and force in the distal flexion condition and in the other two conditions there was a trend towards improving force predictions with high pass filtering. The degree of linearity differed between the three contraction conditions and high pass filtering improved the linearity in all conditions. Non-linear normalization had greater impact on the EMG-force relationship than high pass filtering. The difference in optimal processing parameters suggests that high pass filtering and linearity are dependent on contraction mode as well as the muscle analyzed.
Optimal noise filtering in the chemotactic response of Escherichia coli.
Directory of Open Access Journals (Sweden)
Burton W Andrews
2006-11-01
Full Text Available Information-carrying signals in the real world are often obscured by noise. A challenge for any system is to filter the signal from the corrupting noise. This task is particularly acute for the signal transduction network that mediates bacterial chemotaxis, because the signals are subtle, the noise arising from stochastic fluctuations is substantial, and the system is effectively acting as a differentiator which amplifies noise. Here, we investigated the filtering properties of this biological system. Through simulation, we first show that the cutoff frequency has a dramatic effect on the chemotactic efficiency of the cell. Then, using a mathematical model to describe the signal, noise, and system, we formulated and solved an optimal filtering problem to determine the cutoff frequency that bests separates the low-frequency signal from the high-frequency noise. There was good agreement between the theory, simulations, and published experimental data. Finally, we propose that an elegant implementation of the optimal filter in combination with a differentiator can be achieved via an integral control system. This paper furnishes a simple quantitative framework for interpreting many of the key notions about bacterial chemotaxis, and, more generally, it highlights the constraints on biological systems imposed by noise.
About one problem of optimal stabilization of linear compound systems
Directory of Open Access Journals (Sweden)
Barseghyan V.R.
2014-12-01
Full Text Available The problem of optimal stabilization of linear compound system is investigated. Based on Lyapunov function method the method of building optimal stabilizing control action is suggested. The solution of the problem of optimal stabilization of a concrete compound system is given.
Joint Linear Filter Design in Multiuser Cooperative Nonregenerative MIMO Relay Systems
Directory of Open Access Journals (Sweden)
Li Gen
2009-01-01
Full Text Available This paper addresses the filter design issues for multiuser cooperative nonregenerative MIMO relay systems in both downlink and uplink scenarios. Based on the formulated signal model, the filter matrix optimization is first performed for direct path and relay path respectively, aiming to minimize the mean squared error (MSE. To be more specific, for the relay path, we derive the local optimal filter scheme at the base station and the relay station jointly in the downlink scenario along with a more practical suboptimal scheme, and then a closed-form joint local optimal solution in the uplink scenario is exploited. Furthermore, the optimal filter for the direct path is also presented by using the exiting results of conventional MIMO link. After that, several schemes are proposed for cooperative scenario to combine the signals from both paths. Numerical results show that the proposed schemes can reduce the bit error rate (BER significantly.
Shen, Mouquan; Park, Ju H
2016-07-01
This paper addresses the H∞ filtering of continuous Markov jump linear systems with general transition probabilities and output quantization. S-procedure is employed to handle the adverse influence of the quantization and a new approach is developed to conquer the nonlinearity induced by uncertain and unknown transition probabilities. Then, sufficient conditions are presented to ensure the filtering error system to be stochastically stable with the prescribed performance requirement. Without specified structure imposed on introduced slack variables, a flexible filter design method is established in terms of linear matrix inequalities. The effectiveness of the proposed method is validated by a numerical example.
Energy Technology Data Exchange (ETDEWEB)
Jin Yongxing; Dong Xinyong; Wang Jianfeng [Institute of Optoelectronic Technology, China Jiliang University, Hangzhou (China); Zhou Junqiang, E-mail: phyjyxin@gmail.com [Network Technology Research Centre, Nanyang Technological University (Singapore)
2011-02-01
In this paper, a continuously tunable microwave photonic notch filter is proposed and experimentally demonstrated. This filter is based on the differential group delay generated by a high-birefringence linearly chirped fiber Bragg grating. This microwave photonic filter belongs to the orthogonal polarization approach, polarization maintaining structure ensures the filter free from the random optical interference problem. Its response is induced by the differential group delay (DGD) of the Hi-Bi LCFBG and it can be varied by tuning the grating through adding gradient strength to the grating. Free spectral range tuning by 9.27 GHz with more than 35 dB notch rejection is achieved.
A Low Power Linear Phase Digital FIR Filter for Wearable ECG Devices.
Lian, Yong; Yu, Jianghong
2005-01-01
In this paper we present a low power linear phase digital FIR filter which is a part of an ECG-on-Chip. The ECG-on-Chip can be embedded into clothing to acquire the electrocardiogram (ECG) signal and send a warning message to a mobile phone or PDA if an abnormal ECG is detected. The proposed new filter structure significantly reduces the arithmetic operations for each sample which in turn lowers the power consumption. The filter is developed based on the interpolated finite impulse filter technique and is very attractive for a low cost and low power VLSI implementation.
On optimal output regulation for linear systems
Saberi, Ali; Stoorvogel, Anton A.; Sannuti, Peddapullaiah; Shi, Guoyong
2003-01-01
The classical output regulation problem formulation for linear systems has a number of shortcomings; among them a primary one is that it does not take into account the transient response. Although this problem has been studied since the 1970s, a complete picture has not emerged yet. We formulate and
On Optimal Fault Detection for Discrete-time Markovian Jump Linear Systems
Institute of Scientific and Technical Information of China (English)
LI Yue-Yang; ZHONG Mai-Ying
2013-01-01
This paper deals with the problem of fault detection for discrete-time Markovian jump linear systems (MJLS).Using an observer-based fault detection filter (FDF) as a residual generator,the design of the FDF is formulated as an optimization problem for maximizing stochastic H_/H∞ or H∞/H∞ performance index.With the aid of an operator optimization method,it is shown that a unified optimal solution can be derived by solving a coupled Riccati equation.Numerical examples are given to show the effectiveness of the proposed method.
Design of FIR Filters with Discrete Coefficients using Ant Colony Optimization
Tsutsumi, Shuntaro; Suyama, Kenji
In this paper, we propose a new design method for linear phase FIR (Finite Impulse Response) filters with discrete coefficients. In a hardware implementation, filter coefficients must be represented as discrete values. The design problem of digital filters with discrete coefficients is formulated as the integer programming problem. Then, an enormous amount of computational time is required to solve the problem in a strict solver. Recently, ACO (Ant Colony Optimization) which is one heuristic approach, is used widely for solving combinational problem like the traveling salesman problem. In our method, we formulate the design problem as the 0-1 integer programming problem and solve it by using the ACO. Several design examples are shown to present effectiveness of the proposed method.
H∞ deconvolution filter design for time-delay linear continuous-time systems
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Proposes an H∞ deconvolution design for time-delay linear continuous-time systems. We first analyze the general structure and innovation structure of the H∞ deconvolution filter. The deconvolution filter with innovation structure is made up of an output observer and a linear mapping, where the latter reflects the internal connection between the unknown input signal and the output estimate error. Based on the bounded real lemma,a time domain design approach and a sufficient condition for the existence of deconvolution filter are presented.The parameterization of the deconvolution filter can be completed by solving a Riccati equation. The proposed method is useful for the case that does not require statistical information about disturbances. At last, a numerical example is given to demonstrate the performance of the proposed filter.
Directory of Open Access Journals (Sweden)
Ebrahim Borzabadi
2012-01-01
Full Text Available The aim of this paper is the introduction of a CMOS OTA basic block that its transconductance gain can be electronically and linearly tuned. This transconductance is proportional to the square root of the bias current. To achieve the maximum output voltage and create a wide range of linear transconductance the CMOS OTA has been used.Then the variation of the transconductance and its effects on the performance of Continuous-time filters has been considered. The novelty of this paper is to show that how the transconductance of a first-Order filter is transformed to high pass and low pass filters and the transfer function of a second-order filter is transformed into high pass, low pass , band pass and band rejection filters. The performance of the proposed circuit is discussed and confirmed through MATLAB and PSPICE-simulation results.
Mandal, J K
2012-01-01
In this paper a novel approach for de noising images corrupted by random valued impulses has been proposed. Noise suppression is done in two steps. The detection of noisy pixels is done using all neighbor directional weighted pixels (ANDWP) in the 5 x 5 window. The filtering scheme is based on minimum variance of the four directional pixels. In this approach, relatively recent category of stochastic global optimization technique i.e., particle swarm optimization (PSO) has also been used for searching the parameters of detection and filtering operators required for optimal performance. Results obtained shows better de noising and preservation of fine details for highly corrupted images.
Directory of Open Access Journals (Sweden)
Chinda Samakee
2012-12-01
Full Text Available Recently, many publications reported the generation of subharmonic frequency (f0/2 and its potential use in imagingfrom ultrasound contrast agent (UCA. Subharmonic imaging (SHI has provided better contrast resolution over the secondharmonic signals due to the lack of subharmonic generation in the tissue region. However, subharmonic separation in SHIutilizes linear bandpass filtering only. In this paper, we compare the subharmonic separation capability of linear band filter(LBF, pulse inversion (PI, and their combination (PILBF based on contrast-to-tissue ratio (CTR. Results show that theCTR values from the LBF, the PI, and the PILBF are 20.30, 40.30, and 52.74 dB, respectively. The optimal stopband attenuation and fractional bandwidth for the PILBF method are 50 dB and 10%, respectively. This high CTR value indicates thefeasibility of the PILBF method in creating high quality ultrasound image from subharmonic frequency.
Recursive inversion of externally defined linear systems by FIR filters
Bach, Ralph E., Jr.; Baram, Yoram
1989-01-01
The approximate inversion of an internally unknown linear system, given by its impulse response sequence, by an inverse system having a finite impulse response, is considered. The recursive least-squares procedure is shown to have an exact initialization, based on the triangular Toeplitz structure of the matrix involved. The proposed approach also suggests solutions to the problem of system identification and compensation.
Optimal Differentiation Pricing Policy with Linear Demand Function
Institute of Scientific and Technical Information of China (English)
唐小我; 张明善
2003-01-01
The main objective in any marketing effort is to consider the optimal conditions to maximize revenue and profit. The optimal market segmentation pricing strategy is investigated under the assumption of an aggregate linear demand function. The optimal conditions to maximize revenue and profit, two closely correlative problems, are obtained respectively. The differentiation pricing policy described here can be easily applied in practice. A numerical example is provided which vividly illustrates the advantage of applying optimal policies.
Semi-active optimal control of linearized systems with multi-degree of freedom and application
Ying, Z. G.; Ni, Y. Q.; Ko, J. M.
2005-01-01
A semi-active optimal control method for non-linear multi-degree-of-freedom systems and its application to a building structure for random response reduction are presented in this paper. A structural system with semi-active control devices under random loading is modelled as a controlled, randomly excited and dissipated Hamiltonian system of multi-degree of freedom. The control force produced by a semi-active control device is split into semi-active part and passive part incorporated in the uncontrolled system. Applying the statistical linearization method to the non-linear multi-degree-of-freedom system with passive control force components yields quasi-linear equations of motion, which can tend to corresponding linear ones with system response reduction. By applying the dynamical programming principle to the controlled linearized system, a dynamical programming equation is established and in particular, for a non-filtering white noise excitation, is solved as an optimal regulation problem to determine the quasi-linear quadratic optimal control law and furthermore semi-active optimal control law according to the variational principle. Then the semi-active optimal control of a tall building structure with magnetorheological-tuned liquid column damper (MR-TLCD) under random wind excitation is performed by using the proposed method. The non-linear model of the structural system with semi-active MR-TLCD is formulated in structural mode space and uncoupled between structural and MR fluid accelerations. The quasi-linear equations for system states are derived from the model and the dynamical programming equation for the system is obtained. In the case that the random wind excitation with the Davenport power spectrum cannot be modelled as a linear filtering white noise, the dynamical programming equation is solved as an optimal regulation problem to obtain the semi-active optimal control force, on which the clipping treatment may be performed to ensure the control force
Adaptive Non-Linear Bayesian Filter for ECG Denoising
Directory of Open Access Journals (Sweden)
Mitesh Kumar Sao
2014-06-01
Full Text Available The cycles of an electrocardiogram (ECG signal contain three components P-wave, QRS complex and the T-wave. Noise is present in cardiograph as signals being measured in which biological resources (muscle contraction, base line drift, motion noise and environmental resources (power line interference, electrode contact noise, instrumentation noise are normally pollute ECG signal detected at the electrode. Visu-Shrink thresholding and Bayesian thresholding are the two filters based technique on wavelet method which is denoising the PLI noisy ECG signal. So thresholding techniques are applied for the effectiveness of ECG interval and compared the results with the wavelet soft and hard thresholding methods. The outputs are evaluated by calculating the root mean square (RMS, signal to noise ratio (SNR, correlation coefficient (CC and power spectral density (PSD using MATLAB software. The clean ECG signal shows Bayesian thresholding technique is more powerful algorithm for denoising.
Grey Box Non-Linearities Modeling and Characterization of a BandPass BAW Filter
Directory of Open Access Journals (Sweden)
M. Mabrouk
2016-06-01
Full Text Available In this work, the non-linearities of a 3G/UMTS geared BandPass Bulk Acoustic Wave ladder filter composed of five resonators were modeled using non-linear modified Butterworth-Van Dyke model. The non-linear characteristics were measured and simulated, and they were compared and found to be fairly identical. The filter's central frequency is 2.12 GHz, the corresponding bandwidth is 61.55 MHz, and the quality factor is 34.55.
Finite-time H∞ filtering for non-linear stochastic systems
Hou, Mingzhe; Deng, Zongquan; Duan, Guangren
2016-09-01
This paper describes the robust H∞ filtering analysis and the synthesis of general non-linear stochastic systems with finite settling time. We assume that the system dynamic is modelled by Itô-type stochastic differential equations of which the state and the measurement are corrupted by state-dependent noises and exogenous disturbances. A sufficient condition for non-linear stochastic systems to have the finite-time H∞ performance with gain less than or equal to a prescribed positive number is established in terms of a certain Hamilton-Jacobi inequality. Based on this result, the existence of a finite-time H∞ filter is given for the general non-linear stochastic system by a second-order non-linear partial differential inequality, and the filter can be obtained by solving this inequality. The effectiveness of the obtained result is illustrated by a numerical example.
Design optimization of a linear actuator
DEFF Research Database (Denmark)
Rechenbach, B.; Willatzen, Morten; Preisler, K. Lorenzen
2013-01-01
The mechanical contacting of a dielectric elastomer actuator is investigated. The actuator is constructed by coiling the dielectric elastomer around two parallel metal rods, similar to a rubber band stretched by two index fingers. The goal of this paper is to design the geometry and the mechanical...... properties of a polymeric interlayer between the elastomer and the rods, gluing all materials together, so as to optimize the mechanical durability of the system. Finite element analysis is employed for the theoretical study which is linked up to experimental results performed by Danfoss PolyPower A/S....
Newtonian Nonlinear Dynamics for Complex Linear and Optimization Problems
Vázquez, Luis
2013-01-01
Newtonian Nonlinear Dynamics for Complex Linear and Optimization Problems explores how Newton's equation for the motion of one particle in classical mechanics combined with finite difference methods allows creation of a mechanical scenario to solve basic problems in linear algebra and programming. The authors present a novel, unified numerical and mechanical approach and an important analysis method of optimization. This book also: Presents mechanical method for determining matrix singularity or non-independence of dimension and complexity Illustrates novel mathematical applications of classical Newton’s law Offers a new approach and insight to basic, standard problems Includes numerous examples and applications Newtonian Nonlinear Dynamics for Complex Linear and Optimization Problems is an ideal book for undergraduate and graduate students as well as researchers interested in linear problems and optimization, and nonlinear dynamics.
A novel method of drift-scanning stars suppression based on the standardized linear filter
Lin, Jianlin; Ping, Xijian; Hou, Guanghua; Ma, Debao
2011-11-01
A large number of stars in the drift-scanning star image have interfered with the detection of small target, this paper proposes an adaptive linear filtering method to achieve the small target detection by suppressing the stars. Firstly, the characteristics of stars, interest target and noise three different representative objects in the star image are analyzed, then the standardized linear filter is constructed to suppress the stars. For the purpose of decreasing the influence region of stars filtering uniformly, a gradient linear filter is constructed to modify the stars suppression method with the standardized linear filter. Then the filter parameter selection method is given. Finally, a multi-frame target track experiment on the real drift-scanning data is made to testify the validity of the proposed method. With the processing results of different methods, it has been showed that the proposed method for suppressing stars with different length and lean angle has a better effect, higher robustness and easier application than the others.
Interlaced optimal-REQUEST and unscented Kalman filtering for attitude determination
Institute of Scientific and Technical Information of China (English)
Quan Wei; Xu Liang; Zhang Huijuan; Fang Jiancheng
2013-01-01
Aimed at low accuracy of attitude determination because of using low-cost components which may result in non-linearity in integrated attitude determination systems,a novel attitude determination algorithm using vector observations and gyro measurements is presented.The various features of the unscented Kalman filter (UKF) and optimal-REQUEST (quaternion estimator) algorithms are introduced for attitude determination.An interlaced filtering method is presented for the attitude determination of nano-spacecraft by setting the quaternion as the attitude representation,using the UKF and optimal-REQUEST to estimate the gyro drifts and the quaternion,respectively.The optimal-REQUEST and UKF are not isolated from each other.When the optimal-REQUEST algorithm estimates the attitude quaternion,the gyro drifts are estimated by the UKF algorithm synchronously by using the estimated attitude quaternion.Furthermore,the speed of attitude determination is improved by setting the state dimension to three.Experimental results show that the presented method has higher performance in attitude determination compared to the UKF algorithm and the traditional interlaced filtering method and can estimate the gyro drifts quickly.
Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition
Meckley, John R.
1995-09-01
The information content in many signal processing applications can be reduced to a set of linear features in a 2D signal transform. Examples include the narrowband lines in a spectrogram, ship wakes in a synthetic aperture radar image, and blood vessels in a medical computer-aided tomography scan. The line integrals that generate the values of the projections of the Radon transform can be characterized as a bank of matched filters for linear features. This localization of energy in the Radon transform for linear features can be exploited to enhance these features and to reduce noise by filtering the Radon transform with a filter explicitly designed to pass only linear features, and then reconstructing a new 2D signal by inverting the new filtered Radon transform (i.e., via filtered backprojection). Previously used methods for filtering the Radon transform include Fourier based filtering (a 2D elliptical Gaussian linear filter) and a nonlinear filter ((Radon xfrm)**y with y >= 2.0). Both of these techniques suffer from the mismatch of the filter response to the true functional form of the Radon transform of a line. The Radon transform of a line is not a point but is a function of the Radon variables (rho, theta) and the total line energy. This mismatch leads to artifacts in the reconstructed image and a reduction in achievable processing gain. The Radon transform for a line is computed as a function of angle and offset (rho, theta) and the line length. The 2D wavelet coefficients are then compared for the Haar wavelets and the Daubechies wavelets. These filter responses are used as frequency filters for the Radon transform. The filtering is performed on the wavelet pyramid decomposition of the Radon transform by detecting the most likely positions of lines in the transform and then by convolving the local area with the appropriate response and zeroing the pyramid coefficients outside of the response area. The response area is defined to contain 95% of the total
Improved Rao-Blackwellized Particle Filter by Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Zeng-Shun Zhao
2013-01-01
Full Text Available The Rao-Blackwellized particle filter (RBPF algorithm usually has better performance than the traditional particle filter (PF by utilizing conditional dependency relationships between parts of the state variables to estimate. By doing so, RBPF could not only improve the estimation precision but also reduce the overall computational complexity. However, the computational burden is still too high for many real-time applications. To improve the efficiency of RBPF, the particle swarm optimization (PSO is applied to drive all the particles to the regions where their likelihoods are high in the nonlinear area. So only a small number of particles are needed to participate in the required computation. The experimental results demonstrate that this novel algorithm is more efficient than the standard RBPF.
Multidimensional indexing structure for use with linear optimization queries
Bergman, Lawrence David (Inventor); Castelli, Vittorio (Inventor); Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Smith, John Richard (Inventor)
2002-01-01
Linear optimization queries, which usually arise in various decision support and resource planning applications, are queries that retrieve top N data records (where N is an integer greater than zero) which satisfy a specific optimization criterion. The optimization criterion is to either maximize or minimize a linear equation. The coefficients of the linear equation are given at query time. Methods and apparatus are disclosed for constructing, maintaining and utilizing a multidimensional indexing structure of database records to improve the execution speed of linear optimization queries. Database records with numerical attributes are organized into a number of layers and each layer represents a geometric structure called convex hull. Such linear optimization queries are processed by searching from the outer-most layer of this multi-layer indexing structure inwards. At least one record per layer will satisfy the query criterion and the number of layers needed to be searched depends on the spatial distribution of records, the query-issued linear coefficients, and N, the number of records to be returned. When N is small compared to the total size of the database, answering the query typically requires searching only a small fraction of all relevant records, resulting in a tremendous speedup as compared to linearly scanning the entire dataset.
Second-Order Cone Formulations of Mixed-Norm Error Constraints for FIR Filter Optimization
2010-06-25
length N an approximate rule of thumb for the minimum grid spacing is 1/(20N). If E is a real-valued function, representing a linear- phase filter , then...well as the general Lp solution. The filter has 35 real coefficients with no symmetry and a reduced passband delay (relative to a linear phase filter ) of
Energy Technology Data Exchange (ETDEWEB)
Pike, D.H.; Morrison, G.W.; Westley, G.W.
1977-10-01
The feasibility of using modern state estimation techniques (specifically Kalman Filtering and Linear Smoothing) to detect losses of material from material balance areas is evaluated. It is shown that state estimation techniques are not only feasible but in most situations are superior to existing methods of analysis. The various techniques compared include Kalman Filtering, linear smoothing, standard control charts, and average cumulative summation (CUSUM) charts. Analysis results indicated that the standard control chart is the least effective method for detecting regularly occurring losses. An improvement in the detection capability over the standard control chart can be realized by use of the CUSUM chart. Even more sensitivity in the ability to detect losses can be realized by use of the Kalman Filter and the linear smoother. It was found that the error-covariance matrix can be used to establish limits of error for state estimates. It is shown that state estimation techniques represent a feasible and desirable method of theft detection. The technique is usually more sensitive than the CUSUM chart in detecting losses. One kind of loss which is difficult to detect using state estimation techniques is a single isolated loss. State estimation procedures are predicated on dynamic models and are well-suited for detecting losses which occur regularly over several accounting periods. A single isolated loss does not conform to this basic assumption and is more difficult to detect.
ANOTHER LOOK AT LINEAR-QUADRATIC OPTIMIZATION PROBLEMS OVER TIME
NIEUWENHUIS, JW
1995-01-01
We will study deterministic quadratic optimization problems over time with linear constraints by means of the behavioral approach of linear systems as developed by Willems (1986, 1989). We will start with a simple example from economics and embed this in a general framework. Then we will develop the
The Uniqueness of Optimal Solution for Linear Programming Problem
Institute of Scientific and Technical Information of China (English)
QuanlingWei; HongYan; JunWang
2004-01-01
This paper investigates an old problem in operations research, the uniqueness of the optimal solution to a linear programming problem. We discuss the problem on a general polyhedron, give some equivalent conditions for uniqueness testing. In addition, we discuss the implementation issues for linear programming based decision making procedures,which motivated this research.
Asynchronous H∞ filtering for linear switched systems with average dwell time
Wang, Bo; Zhang, Hongbin; Wang, Gang; Dang, Chuangyin
2016-09-01
This paper is concerned with the H∞ filtering problem for a class of continuous-time linear switched systems with the asynchronous behaviours, where 'asynchronous' means that the switching of the filters to be designed has a lag to the switching of the system modes. By using the Lyapunov-like functions and the average dwell time technique, a sufficient condition is obtained to guarantee the asymptotic stability with a weighted H∞ performance index for the filtering error system. Moreover, the results are formulated in the form of linear matrix inequalities that are numerical feasible. As a result, the filter design problem is solved. Finally, an illustrative numerical example is presented to show the effectiveness of the results.
Identification of linear continuous-time system using wavelet modulating filters
Institute of Scientific and Technical Information of China (English)
贺尚红; 钟掘
2004-01-01
An approach to identification of linear continuous-time system is studied with modulating functions. Based on wavelet analysis theory, the multi-resolution modulating functions are designed, and the corresponding filters have been analyzed. Using linear modulating filters, we can obtain an identification model that is parameterized directly in continuous-time model parameters. By applying the results from discrete-time model identification to the obtained identification model, a continuous-time estimation method is developed. Considering the accuracy of parameter estimates, an instrumental variable(V) method is proposed, and the design of modulating integral filter is discussed. The relationship between the accuracy of identification and the parameter of modulating filter is investigated, and some points about designing Gaussian wavelet modulating function are outlined. Finally, a simulation study is also included to verify the theoretical results.
RF Circuit linearity optimization using a general weak nonlinearity model
Cheng, W.; Oude Alink, M.S.; Annema, Anne J.; Croon, Jeroen A.; Nauta, Bram
2012-01-01
This paper focuses on optimizing the linearity in known RF circuits, by exploring the circuit design space that is usually available in today’s deep submicron CMOS technologies. Instead of using brute force numerical optimizers we apply a generalized weak nonlinearity model that only involves AC
Lifted linear phase filter banks and the polyphase-with-advance representation
Energy Technology Data Exchange (ETDEWEB)
Brislawn, C. M. (Christopher M.); Wohlberg, B. E. (Brendt E.)
2004-01-01
A matrix theory is developed for the noncausal polyphase-with-advance representation that underlies the theory of lifted perfect reconstruction filter banks and wavelet transforms as developed by Sweldens and Daubechies. This theory provides the fundamental lifting methodology employed in the ISO/IEC JPEG-2000 still image coding standard, which the authors helped to develop. Lifting structures for polyphase-with-advance filter banks are depicted in Figure 1. In the analysis bank of Figure 1(a), the first lifting step updates x{sub 0} with a filtered version of x{sub 1} and the second step updates x{sub 1} with a filtered version of x{sub 0}; gain factors 1/K and K normalize the lowpass- and highpass-filtered output subbands. Each of these steps is inverted by the corresponding operations in the synthesis bank shown in Figure 1(b). Lifting steps correspond to upper- or lower-triangular matrices, S{sub i}(z), in a cascade-form decomposition of the polyphase analysis matrix, H{sub a}(z). Lifting structures can also be implemented reversibly (i.e., losslessly in fixed-precision arithmetic) by rounding the lifting updates to integer values. Our treatment of the polyphase-with-advance representation develops an extensive matrix algebra framework that goes far beyond the results of. Specifically, we focus on analyzing and implementing linear phase two-channel filter banks via linear phase lifting cascade schemes. Whole-sample symmetric (WS) and half-sample symmetric (HS) linear phase filter banks are characterized completely in terms of the polyphase-with-advance representation. The theory benefits significantly from a number of new group-theoretic structures arising in the polyphase-with-advance matrix algebra from the lifting factorization of linear phase filter banks.
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA
Hafez, Samir F.; Selim, Mazen M.; Hala H. Zayed
2015-01-01
We present a new approach for face recognition system. The method is based on 2D face image features using subset of non-correlated and Orthogonal Gabor Filters instead of using the whole Gabor Filter Bank, then compressing the output feature vector using Linear Discriminant Analysis (LDA). The face image has been enhanced using multi stage image processing technique to normalize it and compensate for illumination variation. Experimental results show that the proposed system is effective for ...
Optimizing Fungal DNA Extraction Methods from Aerosol Filters
Jimenez, G.; Mescioglu, E.; Paytan, A.
2016-12-01
Fungi and fungal spores can be picked up from terrestrial ecosystems, transported long distances, and deposited into marine ecosystems. It is important to study dust-borne fungal communities, because they can stay viable and effect the ambient microbial populations, which are key players in biogeochemical cycles. One of the challenges of studying dust-borne fungal populations is that aerosol samples contain low biomass, making extracting good quality DNA very difficult. The aim of this project was to increase DNA yield by optimizing DNA extraction methods. We tested aerosol samples collected from Haifa, Israel (polycarbonate filter), Monterey Bay, CA (quartz filter) and Bermuda (quartz filter). Using the Qiagen DNeasy Plant Kit, we tested the effect of altering bead beating times and incubation times, adding three freeze and thaw steps, initially washing the filters with buffers for various lengths of time before using the kit, and adding a step with 30 minutes of sonication in 65C water. Adding three freeze/thaw steps, adding a sonication step, washing with a phosphate buffered saline overnight, and increasing incubation time to two hours, in that order, resulted in the highest increase in DNA for samples from Israel (polycarbonate). DNA yield of samples from Monterey (quart filter) increased about 5 times when washing with buffers overnight (phosphate buffered saline and potassium phophate buffer), adding a sonication step, and adding three freeze and thaw steps. Samples collected in Bermuda (quartz filter) had the highest increase in DNA yield from increasing incubation to 2 hours, increasing bead beating time to 6 minutes, and washing with buffers overnight (phosphate buffered saline and potassium phophate buffer). Our results show that DNA yield can be increased by altering various steps of the Qiagen DNeasy Plant Kit protocol, but different types of filters collected at different sites respond differently to alterations. These results can be used as
Design of optimal binary phase and amplitude filters for maximization of correlation peak sharpness
Downie, John D.
1991-01-01
Current binary-phase filters used for optical correlation are usually assumed to have uniform amplitude transmission. Here, a new type of filter is studied, the binary-phase-and-amplitude filter. If binary phase values of 0 and pi are assumed, the amplitude transmittance values of this type of filter can be optimized to maximize the peak sharpness. For a polarization-encoded binary-phase filter this can be translated into optimization of the rotation angle of the output polarizer following the filter-spatial-light modulator. An analytic expression is presented for the optimum polarizer angle and thus for the optimum binary-phase-and-amplitude filter design.
Exactly Recovering Low-Rank Matrix in Linear Time via $l_1$ Filter
Liu, Risheng; Su, Zhixun
2011-01-01
Recovering a low rank matrix from corrupted data, which is known as Robust PCA, has attracted considerable interests in recent years. This problem can be exactly solved by a combined nuclear norm and $l_1$ norm minimization. However, due to the computational burden of SVD inherent with the nuclear norm minimization, traditional methods suffer from high computational complexity, especially for large scale datasets. In this paper, inspired by digital filtering idea in image processing, we propose a novel algorithm, named $l_1$ Filter, for solving Robust PCA with linear cost. The $l_1$ Filter is defined by a seed, which is a exactly recovered small submatrix of the underlying low rank matrix. By solving some $l_1$ minimization problems in parallel, the full low rank matrix can be exactly recovered from corrupted observations with linear cost. Both theoretical analysis and experimental results exhibit that our method is an efficient way to exactly recovering low rank matrix in linear time.
ON THE OPTIMAL CONTROL COMPUTATION OF LINEAR SYSTEMS
Directory of Open Access Journals (Sweden)
H. Tjahjana
2012-05-01
Full Text Available In this paper, we consider a numerical method for designing optimal controlon Linear Quadratic Regulator (LQR problem. In the optimal control design process through Pontryagin Maximum Principle (PMP, we obtain a system of diferential equations in state and costate variables. This system lacks of initial condition on the adjoint variables, and this situation creates classic dificulty for solving optimal control problems.This paper proposes a constructive method to approximate the initial condition of the adjoint system.
ON ALTERNATIVE OPTIMAL SOLUTIONS TO QUASIMONOTONIC PROGRAMMING WITH LINEAR CONSTRAINTS
Institute of Scientific and Technical Information of China (English)
Xue Shengjia
2007-01-01
In this paper, the nonlinear programming problem with quasimonotonic ( both quasiconvex and quasiconcave )objective function and linear constraints is considered. With the decomposition theorem of polyhedral sets, the structure of optimal solution set for the programming problem is depicted. Based on a simplified version of the convex simplex method,the uniqueness condition of optimal solution and the computational procedures to determine all optimal solutions are given, if the uniqueness condition is not satisfied. An illustrative example is also presented.
Superconducting filter with a linear phase for third-generation mobile communications
Energy Technology Data Exchange (ETDEWEB)
Li Fei [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Zhang Xueqiang [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Meng Qingduan [Electronics and Information Engineering Department, Henan University of Science and Technology, Luoyang 471003 (China); Sun Liang [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Zhang Qiang [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Li Chunguang [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Li Shunzhou [Institute of Acoustics, Chinese Academy of Sciences, Beijing 100080 (China); He Aisheng [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); Li Hong [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China); He Yusheng [National Laboratory for Superconductivity, Institute of Physics Chinese Academy of Sciences and Beijing National Laboratory for Condensed Matter Physics, Beijing 100080 (China)
2007-07-15
A linear phase filter using two cross-coupled quadruplet structures to achieve self-equalization was designed at 2012.5 MHz with 5 MHz bandwidth for a third-generation mobile communications system. This filter was fabricated using double-sided YBCO films on a 2 inch diameter, 0.5 mm thick MgO substrate. In the measurement, it showed good matching in the passband, with reflection better than -15 dB. Moreover, the group delay variation is less than 50 ns over 89% of the filter bandwidth.
Ultrafast all-optical clock recovery based on phase-only linear optical filtering
DEFF Research Database (Denmark)
Maram, Reza; Kong, Deming; Galili, Michael
2014-01-01
We report on a novel, efficient technique for all-optical clock recovery from RZ-OOK data signals based on spectral phase-only (all-pass) optical filtering. This technique significantly enhances both the recovered optical clock quality and energy efficiency in comparison with conventional amplitude...... optical filtering approaches using a Fabry-Perot filter. The proposed concept is validated through recovery of the optical clock from a 640 Gbit/s RZ-OOK data signal using a commercial linear optical waveshaper. (C) 2014 Optical Society of America...
Design of Filter for a Class of Switched Linear Neutral Systems
Directory of Open Access Journals (Sweden)
Caiyun Wu
2013-01-01
Full Text Available This paper is concerned with the filtering problem for a class of switched linear neutral systems with time-varying delays. The time-varying delays appear not only in the state but also in the state derivatives. Based on the average dwell time approach and the piecewise Lyapunov functional technique, sufficient conditions are proposed for the exponential stability of the filtering error dynamic system. Then, the corresponding solvability condition for a desired filter satisfying a weighted performance is established. All the conditions obtained are delay-dependent. Finally, two numerical examples are given to illustrate the effectiveness of the proposed theory.
Computation of Optimal Monotonicity Preserving General Linear Methods
Ketcheson, David I.
2009-07-01
Monotonicity preserving numerical methods for ordinary differential equations prevent the growth of propagated errors and preserve convex boundedness properties of the solution. We formulate the problem of finding optimal monotonicity preserving general linear methods for linear autonomous equations, and propose an efficient algorithm for its solution. This algorithm reliably finds optimal methods even among classes involving very high order accuracy and that use many steps and/or stages. The optimality of some recently proposed methods is verified, and many more efficient methods are found. We use similar algorithms to find optimal strong stability preserving linear multistep methods of both explicit and implicit type, including methods for hyperbolic PDEs that use downwind-biased operators.
Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.
Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad
2016-12-01
Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.
Gabor Filter Optimization Design for Iris Texture Analysis
Institute of Scientific and Technical Information of China (English)
Tao Xu; Xing Ming; Xiaoguang Yang
2004-01-01
This paper deals with an optimization design method for the Gabor filters based on the analysis of an iris texture model. By means of analyzing the properties of an iris texture image, the energy distribution regularity of the iris texture image measured by the average power spectrum density is exploited, and the theoretical ranges of the efficient valued frequency and orientation parameters can also be deduced. The analysis shows that the energy distribution of the iris texture is generally centralized around lower frequencies in the spatial frequency domain. Accordingly, an iterative algorithm is designed to optimize the Gabor parameter field. The experimental results indicate the validity of the theory and efficiency of the algorithm.
Stochastic simulation and robust design optimization of integrated photonic filters
Directory of Open Access Journals (Sweden)
Weng Tsui-Wei
2017-01-01
Full Text Available Manufacturing variations are becoming an unavoidable issue in modern fabrication processes; therefore, it is crucial to be able to include stochastic uncertainties in the design phase. In this paper, integrated photonic coupled ring resonator filters are considered as an example of significant interest. The sparsity structure in photonic circuits is exploited to construct a sparse combined generalized polynomial chaos model, which is then used to analyze related statistics and perform robust design optimization. Simulation results show that the optimized circuits are more robust to fabrication process variations and achieve a reduction of 11%–35% in the mean square errors of the 3 dB bandwidth compared to unoptimized nominal designs.
Local Optimality of User Choices and Collaborative Competitive Filtering
Yang, Shuang Hong
2010-01-01
We describe a novel framework for learning recommender models for recommendation systems, which views user-system-item interactions as an opportunity give-and-take process, and encodes both "collaboration" and "competition" mechanisms underlying the interaction. The proposed framework leverages the latent factor models of collaborative filtering to encode "collaboration" (via factor sharing); and in the meanwhile, it utilizes a type of objectives that implies local optimality of user choices to encode "competition". Specifically, it takes into account both the revenue and the opportunity cost of each user decision; and, by optimizing a new objective that are analogous to the economic profit, it encourages that every opportunity being taken by a user be locally the best among the opportunities being offered to him/her. Such competition among candidates opportunities imposes stronger supervision and in turn leads to better generalization to unseen interactions. Empirical results indicates that the collaborative...
A Global Optimization Algorithm for Sum of Linear Ratios Problem
Directory of Open Access Journals (Sweden)
Yuelin Gao
2013-01-01
Full Text Available We equivalently transform the sum of linear ratios programming problem into bilinear programming problem, then by using the linear characteristics of convex envelope and concave envelope of double variables product function, linear relaxation programming of the bilinear programming problem is given, which can determine the lower bound of the optimal value of original problem. Therefore, a branch and bound algorithm for solving sum of linear ratios programming problem is put forward, and the convergence of the algorithm is proved. Numerical experiments are reported to show the effectiveness of the proposed algorithm.
Linearization of Mach-Zehnder modulator using microring-based all-pass filter
Institute of Scientific and Technical Information of China (English)
Jianyi Yang; Fan Wang; Xiaoqing Jiang; Hongchang Qu; Yaming Wu; Minghua Wang; Yuelin Wang
2005-01-01
@@ By applying the microring resonator to the Mach-Zehnder (MZ) optical modulator and employing the super-linear phase change characteristic of the all-pass filter, the sublinear modulation curve of the conventional MZ modulator is highly linearized. With properly controlled power coupling between the microring and the arm of the MZ modulator, the third-order distortion can be suppressed. If the transmission coefficient is set between 0.25 and 0.42, the linearity range larger than 90% can be easily achieved. The maximum linearity range is even up to 99.5%.
An optimal nonorthogonal separation of the anisotropic Gaussian convolution filter.
Lampert, Christoph H; Wirjadi, Oliver
2006-11-01
We give an analytical and geometrical treatment of what it means to separate a Gaussian kernel along arbitrary axes in R(n), and we present a separation scheme that allows us to efficiently implement anisotropic Gaussian convolution filters for data of arbitrary dimensionality. Based on our previous analysis we show that this scheme is optimal with regard to the number of memory accesses and interpolation operations needed. The proposed method relies on nonorthogonal convolution axes and works completely in image space. Thus, it avoids the need for a fast Fourier transform (FFT)-subroutine. Depending on the accuracy and speed requirements, different interpolation schemes and methods to implement the one-dimensional Gaussian (finite impulse response and infinite impulse response) can be integrated. Special emphasis is put on analyzing the performance and accuracy of the new method. In particular, we show that without any special optimization of the source code, it can perform anisotropic Gaussian filtering faster than methods relying on the FFT.
1981-07-01
1p^^i-J\\\\^3^\\\\^. TECHNICAL LIBRARY AD^y^.q ijg. TECHNICAL REPORT ARBRL-TR-02346 COMPUTER ALGORITHMS FOR THE DESIGN AND IMPLEMENTATION OF LINEAR...INSTRUCTIONS BEFORE COMPLETI?>G FORM 1. REPORT NUMBER TECHNICAL REPORT ARBRL-TR-n2.^46 i. GOVT ACCESSION NO. *. TITLE fand Sijfam;»; COMPUTER ... ALGORITHMS FOR THE DESIGN AND IMPLEMENTATION OF LINEAR PHASE FINPTE IMPULSE RESPONSE DIGITAL FILTERS 7. AUTHORf*; James N. Walbert 9
Asymptotic Parameter Estimation for a Class of Linear Stochastic Systems Using Kalman-Bucy Filtering
Directory of Open Access Journals (Sweden)
Xiu Kan
2012-01-01
Full Text Available The asymptotic parameter estimation is investigated for a class of linear stochastic systems with unknown parameter θ:dXt=(θα(t+β(tXtdt+σ(tdWt. Continuous-time Kalman-Bucy linear filtering theory is first used to estimate the unknown parameter θ based on Bayesian analysis. Then, some sufficient conditions on coefficients are given to analyze the asymptotic convergence of the estimator. Finally, the strong consistent property of the estimator is discussed by comparison theorem.
Optimal second order sliding mode control for linear uncertain systems.
Das, Madhulika; Mahanta, Chitralekha
2014-11-01
In this paper an optimal second order sliding mode controller (OSOSMC) is proposed to track a linear uncertain system. The optimal controller based on the linear quadratic regulator method is designed for the nominal system. An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances. To achieve finite time convergence of the sliding mode, a nonsingular terminal sliding surface is added with the integral sliding surface giving rise to a second order sliding mode controller. The main advantage of the proposed OSOSMC is that the control input is substantially reduced and it becomes chattering free. Simulation results confirm superiority of the proposed OSOSMC over some existing.
Directory of Open Access Journals (Sweden)
M. Kumar
2016-01-01
Full Text Available Gaussian noise is one of the dominant noises, which degrades the quality of acquired Computed Tomography (CT image data. It creates difficulties in pathological identification or diagnosis of any disease. Gaussian noise elimination is desirable to improve the clarity of a CT image for clinical, diagnostic, and postprocessing applications. This paper proposes an evolutionary nonlinear adaptive filter approach, using Cat Swarm Functional Link Artificial Neural Network (CS-FLANN to remove the unwanted noise. The structure of the proposed filter is based on the Functional Link Artificial Neural Network (FLANN and the Cat Swarm Optimization (CSO is utilized for the selection of optimum weight of the neural network filter. The applied filter has been compared with the existing linear filters, like the mean filter and the adaptive Wiener filter. The performance indices, such as peak signal to noise ratio (PSNR, have been computed for the quantitative analysis of the proposed filter. The experimental evaluation established the superiority of the proposed filtering technique over existing methods.
Time-dependent switched discrete-time linear systems control and filtering
Zhang, Lixian; Shi, Peng; Lu, Qiugang
2016-01-01
This book focuses on the basic control and filtering synthesis problems for discrete-time switched linear systems under time-dependent switching signals. Chapter 1, as an introduction of the book, gives the backgrounds and motivations of switched systems, the definitions of the typical time-dependent switching signals, the differences and links to other types of systems with hybrid characteristics and a literature review mainly on the control and filtering for the underlying systems. By summarizing the multiple Lyapunov-like functions (MLFs) approach in which different requirements on comparisons of Lyapunov function values at switching instants, a series of methodologies are developed for the issues on stability and stabilization, and l2-gain performance or tube-based robustness for l∞ disturbance, respectively, in Chapters 2 and 3. Chapters 4 and 5 are devoted to the control and filtering problems for the time-dependent switched linear systems with either polytopic uncertainties or measurable time-varying...
Using linear programming to analyze and optimize stochastic flow lines
DEFF Research Database (Denmark)
Helber, Stefan; Schimmelpfeng, Katja; Stolletz, Raik
2011-01-01
This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete tim...... programming and hence allows us to solve buffer allocation problems. We show under which conditions our method works well by comparing its results to exact values for two-machine models and approximate simulation results for longer lines.......This paper presents a linear programming approach to analyze and optimize flow lines with limited buffer capacities and stochastic processing times. The basic idea is to solve a huge but simple linear program that models an entire simulation run of a multi-stage production process in discrete time...
Turnpike theory of continuous-time linear optimal control problems
Zaslavski, Alexander J
2015-01-01
Individual turnpike results are of great interest due to their numerous applications in engineering and in economic theory; in this book the study is focused on new results of turnpike phenomenon in linear optimal control problems. The book is intended for engineers as well as for mathematicians interested in the calculus of variations, optimal control, and in applied functional analysis. Two large classes of problems are studied in more depth. The first class studied in Chapter 2 consists of linear control problems with periodic nonsmooth convex integrands. Chapters 3-5 consist of linear control problems with autonomous nonconvex and nonsmooth integrands. Chapter 6 discusses a turnpike property for dynamic zero-sum games with linear constraints. Chapter 7 examines genericity results. In Chapter 8, the description of structure of variational problems with extended-valued integrands is obtained. Chapter 9 ends the exposition with a study of turnpike phenomenon for dynamic games with extended value integran...
Discrete-time filtering for nonlinear polynomial systems over linear observations
Hernandez-Gonzalez, M.; Basin, M. V.
2014-07-01
This paper designs a discrete-time filter for nonlinear polynomial systems driven by additive white Gaussian noises over linear observations. The solution is obtained by computing the time-update and measurement-update equations for the state estimate and the error covariance matrix. A closed form of this filter is obtained by expressing the conditional expectations of polynomial terms as functions of the estimate and the error covariance. As a particular case, a third-degree polynomial is considered to obtain the finite-dimensional filtering equations. Numerical simulations are performed for a third-degree polynomial system and an induction motor model. Performance of the designed filter is compared with the extended Kalman one to verify its effectiveness.
Ion beam properties after mass filtering with a linear radiofrequency quadrupole
Energy Technology Data Exchange (ETDEWEB)
Ferrer, R., E-mail: Rafael.Ferrer@fys.kuleuven.be [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Kwiatkowski, A.A.; Bollen, G.; Lincoln, D.L. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Department of Physics and Astronomy, East Lansing, MI 48824 (United States); Morrissey, D.J.; Pang, G.K. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Department of Chemistry, East Lansing, MI 48824 (United States); Ringle, R. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Savory, J. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States); Department of Physics and Astronomy, East Lansing, MI 48824 (United States); Schwarz, S. [National Superconducting Cyclotron Laboratory, Michigan State University, East Lansing, MI 48824 (United States)
2014-01-21
The properties of ion beams passing through a linear radiofrequency quadrupole mass filter were investigated with special attention to their dependence on the mass resolving power. Experimentally, an increase of the transverse emittance was observed as the mass-to-charge selectivity of the mass filter was raised. The experimental behavior was confirmed by beam transport simulations. -- Highlights: • The ion-optical properties of a Quadrupole Mass Filter (QMF) are presented. • Measured beam emittances follow a trend to larger values for smaller A/Q ratios and increasing mass resolution. • The experimental behavior was confirmed by beam transport simulations. • The use of a QMF for mass filtering comes at the cost of emittance growth of the ion beam.
Linear filtering with fractional Brownian motion in the signal and observation processes
Directory of Open Access Journals (Sweden)
M. L. Kleptsyna
1999-01-01
Full Text Available Integral equations for the mean-square estimate are obtained for the linear filtering problem, in which the noise generating the signal is a fractional Brownian motion with Hurst index h∈(3/4,1 and the noise in the observation process includes a fractional Brownian motion as well as a Wiener process.
A linear feature space for simultaneous learning of spatio-spectral filters in BCI
Farquhar, J.D.R.
2009-01-01
It is shown how two of the most common types of feature mapping used for classification of single trial Electroencephalography (EEG), i.e. spatial and frequency filtering, can be equivalently performed as linear operations in the space of frequency-specific detector covariance tensors. Thus by first
Acquiring beam data for a flattening-filter free linear accelerator using organic scintillators
DEFF Research Database (Denmark)
Beierholm, Anders Ravnsborg; Behrens, C.F.; Hoffmann, L.;
2013-01-01
-resolved dosimetry on a highly detailed level. In this study, we present beam data for a Varian TrueBeam linear accelerator, which is capable of delivering flattening-filter free (FFF1) clinical X-ray beams. The beam data have been acquired using an in-house developed dosimetry system based on fibre-coupled organic...
Spectral measurement with a linear variable filter using a LMS algorithm
Emadi, A.; Grabarnik, S.; Wu, H.; De Graaf, R.F.; Wolffenbuttel, R.F.
2010-01-01
This paper presents spectral measurements using a linear variable optical filter. A LVOF has been developed for operation in the 530 nm–720 nm spectral band and has been fabricated in an IC-compatible process. The LVOF has been mounted on a CMOS camera. A Least Mean Square algorithm has been
Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation
Kachouie, Nezamoddin N.; Alirezaie, Javad
2005-12-01
Previous approaches to texture analysis and segmentation use multichannel filtering by applying a set of filters in the frequency domain or a set of masks in the spatial domain. This paper presents two new texture segmentation algorithms based on multichannel filtering in conjunction with neural networks for feature extraction and segmentation. The features extracted by Gabor filters have been applied for image segmentation and analysis. Suitable choices of filter parameters and filter bank coverage in the frequency domain to optimize the filters are discussed. Here we introduce two methods to optimize Gabor filter bank. First, a Gabor filter bank with a flat response is implemented and the optimal feature dimension is extracted by competitive networks. Second, a subset of Gabor filter bank is selected to compose the best discriminative filters, so that each filter in this small set can discriminate a pair of textures in a given image. In both approaches, multilayer perceptrons are employed to segment the extracted features. The comparisons of segmentation results generated using the proposed methods and previous research using Gabor, discrete cosine transform (DCT), and Laws filters are presented. Finally, the segmentation results generated by applying the optimized filter banks to textured images are presented and discussed.
Optimized Multichannel Filter Bank with Flat Frequency Response for Texture Segmentation
Directory of Open Access Journals (Sweden)
Kachouie Nezamoddin N
2005-01-01
Full Text Available Previous approaches to texture analysis and segmentation use multichannel filtering by applying a set of filters in the frequency domain or a set of masks in the spatial domain. This paper presents two new texture segmentation algorithms based on multichannel filtering in conjunction with neural networks for feature extraction and segmentation. The features extracted by Gabor filters have been applied for image segmentation and analysis. Suitable choices of filter parameters and filter bank coverage in the frequency domain to optimize the filters are discussed. Here we introduce two methods to optimize Gabor filter bank. First, a Gabor filter bank with a flat response is implemented and the optimal feature dimension is extracted by competitive networks. Second, a subset of Gabor filter bank is selected to compose the best discriminative filters, so that each filter in this small set can discriminate a pair of textures in a given image. In both approaches, multilayer perceptrons are employed to segment the extracted features. The comparisons of segmentation results generated using the proposed methods and previous research using Gabor, discrete cosine transform (DCT, and Laws filters are presented. Finally, the segmentation results generated by applying the optimized filter banks to textured images are presented and discussed.
Linear-phase delay filters for ultra-low-power signal processing in neural recording implants.
Gosselin, Benoit; Sawan, Mohamad; Kerherve, Eric
2010-06-01
We present the design and implementation of linear-phase delay filters for ultra-low-power signal processing in neural recording implants. We use these filters as low-distortion delay elements along with an automatic biopotential detector to perform integral waveform extraction and efficient power management. The presented delay elements are realized employing continuous-time OTA-C filters featuring 9th-order equiripple transfer functions with constant group delay. Such analog delay enables processing neural waveforms with reduced overhead compared to a digital delay since it does not requires sampling and digitization. It uses an allpass transfer function for achieving wider constant-delay bandwidth than all-pole does. Two filters realizations are compared for implementing the delay element: the Cascaded structure and the Inverse follow-the-leader feedback filter. Their respective strengths and drawbacks are assessed by modeling parasitics and non-idealities of OTAs, and by transistor-level simulations. A budget of 200 nA is used in both filters. Experimental measurements with the chosen filter topology are presented and discussed.
Intelligent Optimize Design of LCL Filter for Three-Phase Voltage-Source PWM Rectifier
DEFF Research Database (Denmark)
Sun, Wei; Chen, Zhe; Wu, Xiaojie
2009-01-01
Compared to traditional L filter, a LCL filter is more effective on reducing harmonic distortion at switch frequency. So it is important to choose the LCL filter parameters to achieve good filtering effect. This paper introduces some traditional design methods. Design of a LCL filter by genetic...... algorithm (GA) and particle swam optimization (PSO) are presented in this paper and comparison of the two intelligent optimization. Simulation result and calculate data are provided to prove that intelligent optimization are more effective and simple than traditional methods....
A State-Space Approach to Optimal Level-Crossing Prediction for Linear Gaussian Processes
Martin, Rodney Alexander
2009-01-01
In many complex engineered systems, the ability to give an alarm prior to impending critical events is of great importance. These critical events may have varying degrees of severity, and in fact they may occur during normal system operation. In this article, we investigate approximations to theoretically optimal methods of designing alarm systems for the prediction of level-crossings by a zero-mean stationary linear dynamic system driven by Gaussian noise. An optimal alarm system is designed to elicit the fewest false alarms for a fixed detection probability. This work introduces the use of Kalman filtering in tandem with the optimal level-crossing problem. It is shown that there is a negligible loss in overall accuracy when using approximations to the theoretically optimal predictor, at the advantage of greatly reduced computational complexity. I
Deterministic operations research models and methods in linear optimization
Rader, David J
2013-01-01
Uniquely blends mathematical theory and algorithm design for understanding and modeling real-world problems Optimization modeling and algorithms are key components to problem-solving across various fields of research, from operations research and mathematics to computer science and engineering. Addressing the importance of the algorithm design process. Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems. The result is a clear-cut resource for understanding three cornerstones of deterministic operations resear
Linear Optimization of Frequency Spectrum Assignments Across System
2016-03-01
Instead of separate transmit and receive apertures for each of the multiple radar , communications, and electronic warfare systems, a few pairs of AMRF-C... OPTIMIZATION OF FREQUENCY SPECTRUM ASSIGNMENTS ACROSS SYSTEMS by Steven J. Fischbach March 2016 Thesis Advisor: Jeffrey Hyink Thesis Co-Advisor...March 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE LINEAR OPTIMIZATION OF FREQUENCY SPECTRUM ASSIGNMENTS ACROSS
Optimal linear array heading in a directional noise field
McDonnell, David C.
1992-01-01
Approved for public release; distribution is unlimited. This thesis discusses a procedure that optimizes the signal-to-noise ratio (SNR) detected by a linear array in a directional ambient noise field. The SNR can be optimized by minimizing the ambient noise detected by the array. For a given target location, each possible heading of the array centers the ambiguous beam of the array at a different true bearing. Therefore, each heading of the array will receive a different ambient noise lev...
Multi-objective genetic optimization of linear construction projects
Directory of Open Access Journals (Sweden)
Fatma A. Agrama
2012-08-01
Full Text Available In the real world, the majority cases of optimization problems, met by engineers, are composed of several conflicting objectives. This paper presents an approach for a multi-objective optimization model for scheduling linear construction projects. Linear construction projects have many identical units wherein activities repeat from one unit to another. Highway, pipeline, and tunnels are good examples that exhibit repetitive characteristics. These projects represent a large portion of the construction industry. The present model enables construction planners to generate optimal/near-optimal construction plans that minimize project duration, total work interruptions, and total number of crews. Each of these plans identifies, from a set of feasible alternatives, optimal crew synchronization for each activity and activity interruptions at each unit. This model satisfies the following aspects: (1 it is based on the line of balance technique; (2 it considers non-serial typical activities networks with finish–start relationship and both lag or overlap time between activities is allowed; (3 it utilizes a multi-objective genetic algorithms approach; (4 it is developed as a spreadsheet template that is easy to use. Details of the model with visual charts are presented. An application example is analyzed to illustrate the use of the model and demonstrate its capabilities in optimizing the scheduling of linear construction projects.
Robust Pitch Estimation Using an Optimal Filter on Frequency Estimates
DEFF Research Database (Denmark)
Karimian-Azari, Sam; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2014-01-01
In many scenarios, a periodic signal of interest is often contaminated by different types of noise that may render many existing pitch estimation methods suboptimal, e.g., due to an incorrect white Gaussian noise assumption. In this paper, a method is established to estimate the pitch...... against different noise situations. The simulation results confirm that the proposed MVDR method outperforms the state-of-the-art weighted least squares (WLS) pitch estimator in colored noise and has robust pitch estimates against missing harmonics in some time-frames....... of such signals from unconstrained frequency estimates (UFEs). A minimum variance distortionless response (MVDR) method is proposed as an optimal solution to minimize the variance of UFEs considering the constraint of integer harmonics. The MVDR filter is designed based on noise statistics making it robust...
Mazzà, Claudia; Donati, Marco; McCamley, John; Picerno, Pietro; Cappozzo, Aurelio
2012-01-01
The aim of this study was the fine tuning of a Kalman filter with the intent to provide optimal estimates of lower trunk orientation in the frontal and sagittal planes during treadmill walking at different speeds using measured linear acceleration and angular velocity components represented in a local system of reference. Data were simultaneously collected using both an inertial measurement unit (IMU) and a stereophotogrammetric system from three healthy subjects walking on a treadmill at natural, slow and fast speeds. These data were used to estimate the parameters of the Kalman filter that minimized the difference between the trunk orientations provided by the filter and those obtained through stereophotogrammetry. The optimized parameters were then used to process the data collected from a further 15 healthy subjects of both genders and different anthropometry performing the same walking tasks with the aim of determining the robustness of the filter set up. The filter proved to be very robust. The root mean square values of the differences between the angles estimated through the IMU and through stereophotogrammetry were lower than 1.0° and the correlation coefficients between the corresponding curves were greater than 0.91. The proposed filter design can be used to reliably estimate trunk lateral and frontal bending during walking from inertial sensor data. Further studies are needed to determine the filter parameters that are most suitable for other motor tasks.
A linear programming approach for optimal contrast-tone mapping.
Wu, Xiaolin
2011-05-01
This paper proposes a novel algorithmic approach of image enhancement via optimal contrast-tone mapping. In a fundamental departure from the current practice of histogram equalization for contrast enhancement, the proposed approach maximizes expected contrast gain subject to an upper limit on tone distortion and optionally to other constraints that suppress artifacts. The underlying contrast-tone optimization problem can be solved efficiently by linear programming. This new constrained optimization approach for image enhancement is general, and the user can add and fine tune the constraints to achieve desired visual effects. Experimental results demonstrate clearly superior performance of the new approach over histogram equalization and its variants.
Kuldeep, B; Singh, V K; Kumar, A; Singh, G K
2015-01-01
In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Optimization of linear parametric circuits by the control of stability
Directory of Open Access Journals (Sweden)
Yu. I. Shapovalov
2013-07-01
Full Text Available Introduction. A brief description of the symbolic frequency method for linear parametric circuit analysis is adduced. In particular it comes to parametric transfer functions and assessment of asymptotic stability of such circuits. The formulation of optimization task. The objective function formation is done via two functions - the function of goal defined by desirable circuit characteristics (goal of optimization and function characteristics of circuit defined by the selected values of the varied parameters during optimization of electrical circuit characteristics. The coincidence degree of these two functions is objective function which is formed on their basis by the chosen method. The procedure of optimization. The solution of optimization task is determining the values с0* and m* that provide minimum value of objective function, satisfy the condition of circuit stability and conditions of physical parametric element realizability Example. There is example of single-circuit parametric amplifier optimization using the objective function based on the calculation of parametric circuit transfer function with a symbolic representation of the parametric capacity parameters. Conclusions. Frequency symbolic analysis method allows solving optimization task of parametric linear circuits designing in the frequency domain based on use of the frequency symbolic transfer functions which are approximated by trigonometric polynomials of Fourier, particularly in complex form.
Asymptotically optimal feedback control for a system of linear oscillators
Ovseevich, Alexander; Fedorov, Aleksey
2013-12-01
We consider problem of damping of an arbitrary number of linear oscillators under common bounded control. We are looking for a feedback control steering the system to the equilibrium. The obtained control is asymptotically optimal: the ratio of motion time to zero with this control to the minimum one is close to 1, if the initial energy of the system is large.
CONIC TRUST REGION METHOD FOR LINEARLY CONSTRAINED OPTIMIZATION
Institute of Scientific and Technical Information of China (English)
Wen-yu Sun; Jin-yun Yuan; Ya-xiang Yuan
2003-01-01
In this paper we present a trust region method of conic model for linearly constrainedoptimization problems. We discuss trust region approaches with conic model subproblems.Some equivalent variation properties and optimality conditions are given. A trust regionalgorithm based on conic model is constructed. Global convergence of the method isestablished.
Energy Technology Data Exchange (ETDEWEB)
Sakurai, K.; Shima, H. [OYO Corp., Tokyo (Japan)
1996-10-01
This paper proposes a modeling method of one-dimensional complex resistivity using linear filter technique which has been extended to the complex resistivity. In addition, a numerical test of inversion was conducted using the monitoring results, to discuss the measured frequency band. Linear filter technique is a method by which theoretical potential can be calculated for stratified structures, and it is widely used for the one-dimensional analysis of dc electrical exploration. The modeling can be carried out only using values of complex resistivity without using values of potential. In this study, a bipolar method was employed as a configuration of electrodes. The numerical test of one-dimensional complex resistivity inversion was conducted using the formulated modeling. A three-layered structure model was used as a numerical model. A multi-layer structure with a thickness of 5 m was analyzed on the basis of apparent complex resistivity calculated from the model. From the results of numerical test, it was found that both the chargeability and the time constant agreed well with those of the original model. A trade-off was observed between the chargeability and the time constant at the stage of convergence. 3 refs., 9 figs., 1 tab.
Park, Kihong
2013-02-01
In this paper, we study a two-hop relaying network consisting of one source, one destination, and three amplify-and-forward (AF) relays with multiple antennas. To compensate for the capacity prelog factor loss of 1/2$ due to the half-duplex relaying, alternate transmission is performed among three relays, and the inter-relay interference due to the alternate relaying is aligned to make additional degrees of freedom. In addition, suboptimal linear filter designs at the nodes are proposed to maximize the achievable sum rate for different fading scenarios when the destination utilizes a minimum mean-square error filter. © 1967-2012 IEEE.
Fast polarization-state tracking scheme based on radius-directed linear Kalman filter.
Yang, Yanfu; Cao, Guoliang; Zhong, Kangping; Zhou, Xian; Yao, Yong; Lau, Alan Pak Tao; Lu, Chao
2015-07-27
We propose and experimentally demonstrate a fast polarization tracking scheme based on radius-directed linear Kalman filter. It has the advantages of fast convergence and is inherently insensitive to phase noise and frequency offset effects. The scheme is experimentally compared to conventional polarization tracking methods on the polarization rotation angular frequency. The results show that better tracking capability with more than one order of magnitude improvement is obtained in the cases of polarization multiplexed QPSK and 16QAM signals. The influences of the filter tuning parameters on tracking performance are also investigated in detail.
The Optimal Linear Combination of Multiple Predictors Under the Generalized Linear Models.
Jin, Hua; Lu, Ying
2009-11-15
Multiple alternative diagnostic tests for one disease are commonly available to clinicians. It's important to use all the good diagnostic predictors simultaneously to establish a new predictor with higher statistical utility. Under the generalized linear model for binary outcomes, the linear combination of multiple predictors in the link function is proved optimal in the sense that the area under the receiver operating characteristic (ROC) curve of this combination is the largest among all possible linear combination. The result was applied to analysis of the data from the Study of Osteoporotic Fractures (SOF) with comparison to Su and Liu's approach.
Optimal traffic control in highway transportation networks using linear programming
Li, Yanning
2014-06-01
This article presents a framework for the optimal control of boundary flows on transportation networks. The state of the system is modeled by a first order scalar conservation law (Lighthill-Whitham-Richards PDE). Based on an equivalent formulation of the Hamilton-Jacobi PDE, the problem of controlling the state of the system on a network link in a finite horizon can be posed as a Linear Program. Assuming all intersections in the network are controllable, we show that the optimization approach can be extended to an arbitrary transportation network, preserving linear constraints. Unlike previously investigated transportation network control schemes, this framework leverages the intrinsic properties of the Halmilton-Jacobi equation, and does not require any discretization or boolean variables on the link. Hence this framework is very computational efficient and provides the globally optimal solution. The feasibility of this framework is illustrated by an on-ramp metering control example.
Directory of Open Access Journals (Sweden)
Cătălin LUPU
2014-12-01
Full Text Available This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter, non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting image after applying Canny filter is not ideal. It is possible that the result will be an image with very fragmented edges and many pores in ridge. For the resulting image, a bank of convolution filters are applied one after another (Kirsch, Laplace, Roberts, Prewitt, Sobel, Frei-Chen, averaging convolution filter, circular convolution filter, lapacian convolution filter, gaussian convolution filter, LoG convolution filter, DoG, inverted filters, Wiener, the filter of ”equalization of the power spectrum” (intermediary filter between the Wiener filter and the inverted filter, the geometrical average filter , etc. with different features.
Cusenza, Monica; Accardo, Agostino; Monti, Fabrizio; Bramanti, Placido
2010-01-01
Simultaneous EEG-fMRI is a powerful emerging tool in functional neuroimaging that exploits the relationship between neuronal electrophysiological activity and its hemodynamic response. It has found application in the study of both spontaneous and evoked brain activity. Combining the complementary advantages of the two techniques it provides a measurement with high temporal and spatial resolution, allowing a reliable localization of event generators. However, EEG data recorded inside MRI scanner are heavily corrupted by different types of artifacts due to the interactions between the patient, EEG electrodes wires and the magnetic fields inside the scanner. In particular, gradient switching and RF pulses, necessary to acquire fMRI data, generate large artifacts that can completely obscure EEG signals. Many methods have been proposed to eliminate or at least reduce gradient artifact. In this paper both a qualitative and a quantitative evaluation of two different algorithms used for gradient artifact removal are presented. Linear and non-linear characteristics of EEG, such as power spectra, fractal dimension and beta scaling exponent, are evaluated for EEGs recorded outside and inside the scanner, in MR static and dynamic conditions. The study highlights how residual artifacts after correction and artifacts induced by correction itself could still considerably affect EEG signals. The results suggest that the quality of both these gradient artifact filtering methods is not yet sufficient to preserve EEG characteristics and thus it must be further improved. The aim of this study is to make neurophysiologists aware of the filtering effects that can compromise linear and non-linear analysis of EEG recorded during functional MRI.
Optimal reconstruction of natural images by small sets of Gabor filters
Van Deemter, JH; Cristobal, G
1998-01-01
Images can be reconstructed after being filtered by a Gaussian and a few Gabor filters. Several search methods for the filter parameters for a (near) optimal reconstruction are examined. At first, the search is performed on a 1-D signal which satisfies the radial spectrum of the average of natural i
Finite frequency H_∞ filtering for uncertain discrete-time switched linear systems
Institute of Scientific and Technical Information of China (English)
Dawei Ding; Guanghong Yang
2009-01-01
This paper is concerned with the problem of robust H_∞ filtering for discrete-time switched linear systems with polytopic uncertainties in the finite frequency domain. Based on the generalized Kalman-Yakubovich-Popov (GKYP) iemma and switched parameter-depen-dent Lyapunov functions, a switched full-order filter is designed such that the corresponding filtering error system is asymptotically sta-ble and satisfies a prescribed finite frequency H_∞ performance index. Compared with the existing full frequency approaches, the proposed finite frequency one receives better results for the cases in which the frequency ranges of noises are known. A numerical exam-ple is given to illustrate the effectiveness of the proposed method.
DEFF Research Database (Denmark)
Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik;
2015-01-01
In this paper, we compare the performance of an economically optimizing Nonlinear Model Predictive Controller (E-NMPC) to a linear tracking Model Predictive Controller (MPC) for a spray drying plant. We find in this simulation study, that the economic performance of the two controllers are almost...... equal. We evaluate the economic performance with an industrially recorded disturbance scenario, where unmeasured disturbances and model mismatch are present. The state of the spray dryer, used in the E-NMPC and MPC, is estimated using Kalman Filters with noise covariances estimated by a maximum...
Institute of Scientific and Technical Information of China (English)
王宏健; 王晶; 刘振业
2014-01-01
The location estimated accuracy of Autonomous Underwater Vehicle (AUV) and landmarks decrease because of the degeneracy and impoverishment of samples in standard Fast Simultaneous Localization And Mapping (FastSLAM) algorithm. A improved FastSLAM algorithm based on Iterative Extended Kalman Filter (IEKF) proposal distribution and linear optimization resampling is presented in order to solve this issue. The latest observation is integrated with IEKF in order to decrease the sample degeneracy while the new samples are produced by the linear combination of copied samples and some abandoned ones in order to reduce the sample impoverishment. The kinematic model of AUV, feature model and the measurement models of sensors are all established. And then features are extracted with Hough transform to build the global map. The experiment of the improved FastSLAM algorithm with trial data shows that it can avoid the degeneracy and impoverishment of samples effectively and enhance the location estimation accuracy of AUV and landmarks. Moreover, the consistency analysis showed that the method possesses the consistency of long term.%针对标准快速同步定位与构图(FastSLAM)方法中由于样本退化及贫化导致自主水下航行器(Autonomous Underwater Vehicle, AUV)及路标位置估计精度严重下降的问题，该文提出一种基于迭代扩展 Kalman 滤波(Iterative Extended Kalman Filter, IEKF)建议分布和线性优化重采样的FastSLAM方法，通过IEKF融入最新观测值从而降低样本退化，为了降低样本的贫化，将重采样过程中复制的样本与部分被抛弃的样本通过线性组合产生新样本。建立 AUV 的运动学模型、特征模型及传感器的测量模型，通过 Hough 变换提取特征构建全局地图，采用改进的FastSLAM方法基于海试数据进行了AUV同步定位与构图试验，结果表明该文所设计的方法能够有效避免样本的退化及贫化，提高了AUV及路
Parameter Optimization of Linear Quadratic Controller Based on Genetic Algorithm
Institute of Scientific and Technical Information of China (English)
LI Jimin; SHANG Chaoxuan; ZOU Minghu
2007-01-01
The selection of weighting matrix in design of the linear quadratic optimal controller is an important topic in the control theory. In this paper, an approach based on genetic algorithm is presented for selecting the weighting matrix for the optimal controller. Genetic algorithm is adaptive heuristic search algorithm premised on the evolutionary ideas of natural selection and genetic. In this algorithm, the fitness function is used to evaluate individuals and reproductive success varies with fitness. In the design of the linear quadratic optimal controller, the fitness function has relation to the anticipated step response of the system. Not only can the controller designed by this approach meet the demand of the performance indexes of linear quadratic controller, but also satisfy the anticipated step response of close-loop system. The method possesses a higher calculating efficiency and provides technical support for the optimal controller in engineering application. The simulation of a three-order single-input single-output (SISO) system has demonstrated the feasibility and validity of the approach.
The Optimal Selection for Restricted Linear Models with Average Estimator
Directory of Open Access Journals (Sweden)
Qichang Xie
2014-01-01
Full Text Available The essential task of risk investment is to select an optimal tracking portfolio among various portfolios. Statistically, this process can be achieved by choosing an optimal restricted linear model. This paper develops a statistical procedure to do this, based on selecting appropriate weights for averaging approximately restricted models. The method of weighted average least squares is adopted to estimate the approximately restricted models under dependent error setting. The optimal weights are selected by minimizing a k-class generalized information criterion (k-GIC, which is an estimate of the average squared error from the model average fit. This model selection procedure is shown to be asymptotically optimal in the sense of obtaining the lowest possible average squared error. Monte Carlo simulations illustrate that the suggested method has comparable efficiency to some alternative model selection techniques.
OPTIMIZED AGRICULTURAL PLANNING OF SUGARCANE USING LINEAR PROGRAMMING
Directory of Open Access Journals (Sweden)
Maximiliano Salles Scarpari* and Edgar Gomes Ferreira de Beauclair**
2010-03-01
Full Text Available Optimized agricultural planning is a fundamental activity in business profitability because it can increase the returns from an operation with low additional costs. Nonetheless, the use of operations research adapted to sugarcane plantation management is still limited, resulting in decision-making at management level being primarily empirical. The goal of this work was to develop an optimized planning model for sugarcane farming using a linear programming tool. The program language used was General Algebraic Modelling System (GAMS as this system was seen to be an excellent tool to allow profit maximization and harvesting time schedule optimization in the sugar mill studied. The results presented support this optimized planning model as being a very useful tool for sugarcane management.
Stochastic error whitening algorithm for linear filter estimation with noisy data.
Rao, Yadunandana N; Erdogmus, Deniz; Rao, Geetha Y; Principe, Jose C
2003-01-01
Mean squared error (MSE) has been the most widely used tool to solve the linear filter estimation or system identification problem. However, MSE gives biased results when the input signals are noisy. This paper presents a novel stochastic gradient algorithm based on the recently proposed error whitening criterion (EWC) to tackle the problem of linear filter estimation in the presence of additive white disturbances. We will briefly motivate the theory behind the new criterion and derive an online stochastic gradient algorithm. Convergence proof of the stochastic gradient algorithm is derived making mild assumptions. Further, we will propose some extensions to the stochastic gradient algorithm to ensure faster, step-size independent convergence. We will perform extensive simulations and compare the results with MSE as well as total-least squares in a parameter estimation problem. The stochastic EWC algorithm has many potential applications. We will use this in designing robust inverse controllers with noisy data.
Miniaturized HTS linear phase filter based on neighboring CQ units sharing resonators
Zhang, Tianliang; Yang, Kai; Zhu, Hai; Zhou, Liguo; Jiang, Mingyan; Dang, Wei; Ren, Xiangyang; Hou, Fangyan
2015-10-01
This paper presents a method for using neighboring cascaded quadruplet (CQ) units sharing resonators to decrease the order of filter so as to reduce the size of a high temperature superconducting (HTS) linear phase filter. The main advantage is that it will not reduce the number of the filter’s transmission zeros, and will not increase the difficulty of circuit design and tuning. Based on this method, this paper presents a 10-order HTS linear phase filter with two pairs of transmission zeros on double-sided YBCO/LaAlO3/YBCO films with a size of 20.3 mm × 20.92 mm, a thickness of 0.5 mm and a dielectric constant of 24.04. At 77 K, the filter’s measured center frequency is 830.03 MHz with a bandwidth of 10 MHz, an edge out-of-band rejection greater than 30 dB MHz-1, and a group delay variation of less than ±10 ns over 60% of the filter bandwidth.
A novel optimized LCL-filter designing method for grid connected converter
DEFF Research Database (Denmark)
Guohong, Zeng; Rasmussen, Tonny Wederberg; Teodorescu, Remus
2010-01-01
capacity of all filter components, with clear physical meaning of minimum cost and volume, a set of optimal values of attenuation ratio and inductancesplit- ratio is obtained for deciding all LCL-filter parameters. With this method, filter overall capacity can be minimized while the grid limit of switching......This paper presents a new LCL-filters optimized designing method for grid connected voltage source converter. This method is based on the analysis of converter output voltage components and inherent relations among LCL-filter parameters. By introducing an optimizing index of equivalent total...... frequency distortion is fulfilled. Compared to the existing methods, the proposed method contains only four steps without try-and-error process, so it is efficient and easy to implement. Simulation results of a 50kVA grid-connected inverter with two sets of LCL-filter parameters under different optimizing...
Cong, Fengyu; Leppänen, Paavo H T; Astikainen, Piia; Hämäläinen, Jarmo; Hietanen, Jari K; Ristaniemi, Tapani
2011-09-30
The present study addresses benefits of a linear optimal filter (OF) for independent component analysis (ICA) in extracting brain event-related potentials (ERPs). A filter such as the digital filter is usually considered as a denoising tool. Actually, in filtering ERP recordings by an OF, the ERP' topography should not be changed by the filter, and the output should also be able to be modeled by the linear transformation. Moreover, an OF designed for a specific ERP source or component may remove noise, as well as reduce the overlap of sources and even reject some non-targeted sources in the ERP recordings. The OF can thus accomplish both the denoising and dimension reduction (reducing the number of sources) simultaneously. We demonstrated these effects using two datasets, one containing visual and the other auditory ERPs. The results showed that the method including OF and ICA extracted much more reliable components than the sole ICA without OF did, and that OF removed some non-targeted sources and made the underdetermined model of EEG recordings approach to the determined one. Thus, we suggest designing an OF based on the properties of an ERP to filter recordings before using ICA decomposition to extract the targeted ERP component. Copyright © 2011 Elsevier B.V. All rights reserved.
Linear optical implementation of optimal unambiguous discrimination among quantum states
Institute of Scientific and Technical Information of China (English)
Lu Jing; Zhou Lan; Kuang Le-Man
2006-01-01
In this paper, we present a linear optical scheme for optimal unambiguous discrimination among nonorthogonal quantum states in terms of the multiple-rail and polarization representation of a single photon. In our scheme, discriminated quantum states are expressed by using the spatial degree of freedom of a single photon while the polarization degree of freedom of the single photon is used to act as an auxiliary qubit. The optical components used in our scheme are only passive linear optical elements such as polarizing beam splitters, wave plates, polarizers, single photon detectors,and single photon source.
Cătălin LUPU
2014-01-01
This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter), non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting i...
Cătălin LUPU
2014-01-01
This article presents the development of optimal filters through covolution methods, necessary for restoring, correcting and improving fingerprints acquired from a sensor, able to provide the most ideal image in the output. After the image was binarized and equalized, Canny filter is applied in order to: eliminate the noise (filtering the image with a Gaussian filter), non-maxima suppression, module gradient adaptive binarization and extension edge points edges by hysteresis. The resulting i...
Recovery of systems with a linear filter and nonlinear delay feedback in periodic regimes.
Ponomarenko, V I; Prokhorov, M D
2008-12-01
We propose a set of methods for the estimation of the parameters of time-delay systems with a linear filter and nonlinear delay feedback performing periodic oscillations. The methods are based on an analysis of the system response to regular external perturbations and are valid only for systems whose dynamics can be perturbed. The efficiency of the methods is illustrated using both numerical and experimental data.
Chen, Jing; Liu, Tundong; Jiang, Hao
2016-01-01
A Pareto-based multi-objective optimization approach is proposed to design multichannel FBG filters. Instead of defining a single optimal objective, the proposed method establishes the multi-objective model by taking two design objectives into account, which are minimizing the maximum index modulation and minimizing the mean dispersion error. To address this optimization problem, we develop a two-stage evolutionary computation approach integrating an elitist non-dominated sorting genetic algorithm (NSGA-II) and technique for order preference by similarity to ideal solution (TOPSIS). NSGA-II is utilized to search for the candidate solutions in terms of both objectives. The obtained results are provided as Pareto front. Subsequently, the best compromise solution is determined by the TOPSIS method from the Pareto front according to the decision maker's preference. The design results show that the proposed approach yields a remarkable reduction of the maximum index modulation and the performance of dispersion spectra of the designed filter can be optimized simultaneously.
Energy Technology Data Exchange (ETDEWEB)
Souza, Anderson S.; Rostelato, Maria Elisa C.M.; Zeituni, Carlos A.; Moura, Eduardo S.; Rodrigues, Bruna T.; Souza, Daiane C.; Tiezzi, Rodrigo; Souza, Carla D.; Melo, Emerson R.; Camargo, Anderson R.; Batista, Talita Q., E-mail: asorgatti@hotmail.com, E-mail: elisaros@ipen.br, E-mail: czeituni@ipen.br, E-mail: edusantos_moura@ig.com.br, E-mail: bteigarodrigues@gmail.com, E-mail: dchristini2013@gmail.com, E-mail: rtiezzi@ipen.br, E-mail: carladdsouza@yahoo.com.br, E-mail: s, E-mail: emermelo@hotmail.com, E-mail: anderson.rogerio.c@hotmail.com, E-mail: ta_litterqbatista@hotmail.com [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2015-07-01
This paper discusses the main features associated with the dosimetric parameters between FFF and FF Linacs. A set of Varian TrueBeam Linac and Varian 23EX dosimetric measurements was acquired to perform the experimental measurements. The dose measurements were carried out in a water Blue phantom, with a waterproof ionization chambers: farmer ionization chamber (0.6 cm{sup 3}) and Exradin A1SL(0.053 cm{sup 3}) , for fields 5 x 5, 8 x 8, 10 x 10, 15 x 15, 30 x 30 cm{sup 2}. The 6 MV FFF and FF was the energy used in this work. Percent Depth Dose (PDD) was the dosimetric parameters evaluated using a fixed Source Surface Distance of 100 cm. One depth were applied for the measurements, 10 cm (central axis) from the water surface. The 6 MV FFF showed less penetrating than the 6 MV FF. This is due to the removal flattening filter causes more lower energy photons on the central axis. The field sizes were equivalent for both FFF and FF. The main advantage in operate linear accelerators without flattening filter is due to the high doses rates delivered during the treatment. High doses rates could reduce the patient treatment time and may be beneficial for some treatment techniques such as IMRT and SRT. (author)
Optimal policies for identification of stochastic linear systems
Lopez-Toledo, A. A.; Athans, M.
1975-01-01
The problem of designing closed-loop policies for identification of multiinput-multioutput linear discrete-time systems with random time-varying parameters is considered in this paper using a Bayesian approach. A sensitivity index gives a measure of performance for the closed-loop laws. The computation of the optimal laws is shown to be nontrivial, an exercise in stochastic control, but open-loop, affine, and open-loop feedback optimal inputs are shown to yield tractable problems. Numerical examples are given. For time-invariant systems, the criterion considered is shown to be related to the trace of the information matrix associated with the system.
Cuckoo search optimization for linear antenna arrays synthesis
Directory of Open Access Journals (Sweden)
Ahmed Haffane
2013-01-01
Full Text Available A recently developed metaheuristic optimization algorithm, the Cuckoo search algorithm, is used in this paper for the synthesis of symmetric uniformly spaced linear microstrip antennas array. Cuckoo search is based on the breeding strategy of Cuckoos augmented by a Levy flight behaviour found in the foraging habits of other species. This metaheuristic is tested on amplitude only pattern synthesis and amplitude and phase pattern synthesis. In both case, the objective, is to determinate the optimal excitations element that produce a synthesized radiation pattern within given bounds specified by a pattern mask.
Identification of shear buildings using an instrumental variable method and linear integral filters
Concha, Antonio; Garrido, Rubén; Alvarez-Icaza, Luis
2016-12-01
This paper develops a method for estimating the parameters of a seismically excited building. Acceleration measurements of the ground and of the building floors, containing offsets and noise, are used for identification purposes. The proposed scheme estimates the complete model of the building if all the floors are equipped with accelerometers. Moreover, it also estimates a reduced model of the structure if only some floors are instrumented. The methodology is based on the combined use of the Instrumental Variable method and Linear Integral Filters. The Instrumental Variable method employs as instrument an auxiliary model of the structure, and it is able to directly identify the continuous-time structure model using discrete-time data without resorting on model transformations from continuous-time to discrete-time, and vice-versa. Using Linear Integral Filters allows obtaining a linear in the parameters expression that depends only on acceleration measurements suitable for parameter identification purposes. These filters eliminate measurement offsets and attenuate high-frequency measurement noise. The above features together with the use of the Instrumental variable method reduce the likelihood of biased parameter estimates. Experiments on a testbed employing a reduced-scale five-story structure allow comparing the results obtained using the Instrumental Variable method and those produced by the standard Least Squares method.
Bourgeois, Brian S.; Elmore, Paul A.; Avera, William E.; Zambo, Samantha J.
2016-07-01
This paper examines and contrasts two estimation methods, Kalman filtering and linear smoothing, for creating interpolated data products from bathymetry measurements. Using targeted examples, we demonstrate previously obscured behavior showing the dependence of linear smoothers on the spatial arrangement of the measurements, yielding markedly different estimation results than the Kalman filter. For bathymetry data, we have modified the variance estimates from both the Kalman filter and linear smoothers to obtain comparable estimators for dense data. These comparable estimators produce uncertainty estimates that have statistically insignificant differences via hypothesis testing. Achieving comparable estimation is accomplished by applying the "propagated uncertainty" concept and a numerical realization of Tobler's principle to the measurement data prior to the computation of the estimate. We show new mathematical derivations for these modifications. In addition, we show test results with (a) synthetic data and (b) gridded bathymetry in the area of the Scripps and La Jolla Canyons. Our tenfold cross-validation for case (b) shows that the modified equations create comparable uncertainty for both gridding algorithms with null hypothesis acceptance rates of greater than 99.95% of the data points. In contrast, bilinear interpolation has 10 times the amount of rejection. We then discuss how the uncertainty estimators are, in principle, applicable to interpolate geophysical data other than bathymetry.
Optimal approximation of linear systems by artificial immune response
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.
Global optimization over linear constraint non-convex programming problem
Institute of Scientific and Technical Information of China (English)
ZHANG Gui-Jun; WU Ti-Huan; YE Rong; YANG Hai-qing
2005-01-01
A improving Steady State Genetic Algorithm for global optimization over linear constraint non-convex programmin g problem is presented. By convex analyzing, the primal optimal problem can be converted to an equivalent problem, in which only the information of convex extremes of feasible space is included, and is more easy for GAs to solve. For avoiding invalid genetic operators, a redesigned convex crossover operator is also performed in evolving. As a integrality, the quality of two problem is proven, and a method is also given to get all extremes in linear constraint space. Simulation result show that new algorithm not only converges faster, but also can maintain an diversity population, and can get the global optimum of test problem.
Discrete Time Optimal Adaptive Control for Linear Stochastic Systems
Institute of Scientific and Technical Information of China (English)
JIANG Rui; LUO Guiming
2007-01-01
The least-squares(LS)algorithm has been used for system modeling for a long time. Without any excitation conditions, only the convergence rate of the common LS algorithm can be obtained. This paper analyzed the weighted least-squares(WLS)algorithm and described the good properties of the WLS algorithm. The WLS algorithm was then used for daptive control of linear stochastic systems to show that the linear closed-loop system was globally stable and that the system identification was consistent. Compared to the past optimal adaptive controller,this controller does not impose restricted conditions on the coefficients of the system, such as knowing the first coefficient before the controller. Without any persistent excitation conditions, the analysis shows that, with the regulation of the adaptive control, the closed-loop system was globally stable and the adaptive controller converged to the one-step-ahead optimal controller in some sense.
Optimal adaptive normalized matched filter for large antenna arrays
Kammoun, Abla
2016-09-13
This paper focuses on the problem of detecting a target in the presence of a compound Gaussian clutter with unknown statistics. To this end, we focus on the design of the adaptive normalized matched filter (ANMF) detector which uses the regularized Tyler estimator (RTE) built from N-dimensional observations x, · · ·, x in order to estimate the clutter covariance matrix. The choice for the RTE is motivated by its possessing two major attributes: first its resilience to the presence of outliers, and second its regularization parameter that makes it more suitable to handle the scarcity in observations. In order to facilitate the design of the ANMF detector, we consider the regime in which n and N are both large. This allows us to derive closed-form expressions for the asymptotic false alarm and detection probabilities. Based on these expressions, we propose an asymptotically optimal setting for the regularization parameter of the RTE that maximizes the asymptotic detection probability while keeping the asymptotic false alarm probability below a certain threshold. Numerical results are provided in order to illustrate the gain of the proposed detector over a recently proposed setting of the regularization parameter.
The Optimization of a Microfluidic CTC Filtering Chip by Simulation
Directory of Open Access Journals (Sweden)
Huan Li
2017-03-01
Full Text Available The detection and separation of circulating tumor cells (CTCs are crucial in early cancer diagnosis and cancer prognosis. Filtration through a thin film is one of the size and deformability based separation methods, which can isolate rare CTCs from the peripheral blood of cancer patients regardless of their heterogeneity. In this paper, volume of fluid (VOF multiphase flow models are employed to clarify the cells’ filtering processes. The cells may deform significantly when they enter a channel constriction, which will induce cell membrane stress and damage if the area strain is larger than the critical value. Therefore, the cellular damage criterion characterized by membrane area strain is presented in our model, i.e., the lysis limit of the lipid bilayer is taken as the critical area strain. Under this criterion, we discover that the microfilters with slit-shaped pores do less damage to cells than those with circular pores. The influence of contact angle between the microfilters and blood cells on cellular injury is also discussed. Moreover, the optimal film thickness and flux in our simulations are obtained as 0.5 μm and 0.375 mm/s, respectively. These findings will provide constructive guidance for the improvement of next generation microfilters with higher throughput and less cellular damage.
The linear stability of vertical mixture seepage into the close porous filter with clogging
Maryshev, Boris S.
2017-02-01
In the present paper, filtration of a mixture through a close porous filter is considered. A heavy solute penetrates from the upper side of the filter into the filter body due to seepage flow and diffusion. In the presence of heavy solute a domain with a heavy fluid is formed near the upper boundary of the filter. The stratification, at which the heavy fluid is located above the light, is unstable. When the mass of the heavy solute exceeds the critical value, one can observe the onset of instability. As a result, two regimes of vertical filtration can occur: (1) homogeneous seepage and (2) convective filtration. Filtration of a mixture in porous media is a complex process. It is necessary to take into account the solute immobilization (or sorption) and clogging of porous medium. We consider the case of low solute concentrations, in which the immobilization is described by the linear MIM (mobile/immobile media) model. The clogging is described by the dependence of permeability on porosity in terms of the Carman-Kozeny formula. The presence of immobile (or adsorbed) particles of the solute decreases the porosity of media and porous media becomes less permeable. The purpose of the paper is to find the stability conditions for the homogeneous vertical seepage of the mixture into the close porous filter. The linear stability problem is solved using the quasi-static approach. The critical times of instability are estimated. The stability maps have been plotted in the space of system parameters. The applicability of quasi-static approach is substantiated by direct numerical simulation.
How to Use Linear Programming for Information System Performances Optimization
Directory of Open Access Journals (Sweden)
Hell Marko
2014-09-01
Full Text Available Background: Organisations nowadays operate in a very dynamic environment, and therefore, their ability of continuously adjusting the strategic plan to the new conditions is a must for achieving their strategic objectives. BSC is a well-known methodology for measuring performances enabling organizations to learn how well they are doing. In this paper, “BSC for IS” will be proposed in order to measure the IS impact on the achievement of organizations’ business goals. Objectives: The objective of this paper is to present the original procedure which is used to enhance the BSC methodology in planning the optimal targets of IS performances value in order to maximize the organization's effectiveness. Methods/Approach: The method used in this paper is the quantitative methodology - linear programming. In the case study, linear programming is used for optimizing organization’s strategic performance. Results: Results are shown on the example of a case study national park. An optimal performance value for the strategic objective has been calculated, as well as an optimal performance value for each DO (derived objective. Results are calculated in Excel, using Solver Add-in. Conclusions: The presentation of methodology through the case study of a national park shows that this methodology, though it requires a high level of formalisation, provides a very transparent performance calculation.
Towards minimax policies for online linear optimization with bandit feedback
Bubeck, Sébastien; Kakade, Sham M
2012-01-01
We address the online linear optimization problem with bandit feedback. Our contribution is twofold. First, we provide an algorithm (based on exponential weights) with a regret of order $\\sqrt{d n \\log N}$ for any finite action set with $N$ actions, under the assumption that the instantaneous loss is bounded by 1. This shaves off an extraneous $\\sqrt{d}$ factor compared to previous works, and gives a regret bound of order $d \\sqrt{n \\log n}$ for any compact set of actions. Without further assumptions on the action set, this last bound is minimax optimal up to a logarithmic factor. Interestingly, our result also shows that the minimax regret for bandit linear optimization with expert advice in $d$ dimension is the same as for the basic $d$-armed bandit with expert advice. Our second contribution is to show how to use the Mirror Descent algorithm to obtain computationally efficient strategies with minimax optimal regret bounds in specific examples. More precisely we study two canonical action sets: the hypercub...
Trajectory generation for manipulators using linear quadratic optimal tracking
Directory of Open Access Journals (Sweden)
Olav Egeland
1989-04-01
Full Text Available The reference trajectory is normally known in advance in manipulator control which makes it possible to apply linear quadratic optimal tracking. This gives a control system which rounds corners and generates optimal feedforward. The method may be used for references consisting of straight-line segments as an alternative to the two-step method of using splines to smooth the reference and then applying feedforward. In addition, the method can be used for more complex trajectories. The actual dynamics of the manipulator are taken into account, and this results in smooth and accurate tracking. The method has been applied in combination with the computed torque technique and excellent performance was demonstrated in a simulation study. The method has also been applied experimentally to an industrial spray-painting robot where a saw-tooth reference was tracked. The corner was rounded extremely well, and the steady-state tracking error was eliminated by the optimal feedforward.
Optical transfer function optimization based on linear expansions
Schwiegerling, Jim
2015-09-01
The Optical Transfer Function (OTF) and its modulus the Modulation Transfer Function (MTF) are metrics of optical system performance. However in system optimization, calculation times for the OTF are often substantially longer than more traditional optimization targets such as wavefront error or transverse ray error. The OTF is typically calculated as either the autocorrelation of the complex pupil function or as the Fourier transform of the Point Spread Function. We recently demonstrated that the on-axis OTF can be represented as a linear combination of analytical functions where the weighting terms are directly related to the wavefront error coefficients and apodization of the complex pupil function. Here, we extend this technique to the off-axis case. The expansion technique offers a potential for accelerating OTF optimization in lens design, as well as insight into the interaction of aberrations with components of the OTF.
A linear nonequilibrium thermodynamics approach to optimization of thermoelectric devices
Ouerdane, H; Apertet, Y; Michot, A; Abbout, A
2013-01-01
Improvement of thermoelectric systems in terms of performance and range of applications relies on progress in materials science and optimization of device operation. In this chapter, we focuse on optimization by taking into account the interaction of the system with its environment. For this purpose, we consider the illustrative case of a thermoelectric generator coupled to two temperature baths via heat exchangers characterized by a thermal resistance, and we analyze its working conditions. Our main message is that both electrical and thermal impedance matching conditions must be met for optimal device performance. Our analysis is fundamentally based on linear nonequilibrium thermodynamics using the force-flux formalism. An outlook on mesoscopic systems is also given.
DEFF Research Database (Denmark)
Mohd. Azam, Sazuan Nazrah
2017-01-01
In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing...... dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered...... part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations....
Azam, Sazuan N. M.
2017-01-01
In this paper, we used the modified quadruple tank system that represents a multi-input-multi-output (MIMO) system as an example to present the realization of a linear discrete-time state space model and to obtain the state estimation using Kalman filter in a methodical mannered. First, an existing dynamics of the system of stochastic differential equations is linearized to produce the deterministic-stochastic linear transfer function. Then the linear transfer function is discretized to produce a linear discrete-time state space model that has a deterministic and a stochastic component. The filtered part of the Kalman filter is used to estimates the current state, based on the model and the measurements. The static and dynamic Kalman filter is compared and all results is demonstrated through simulations.
Tyler, Madelaine K; Liu, Paul Z Y; Lee, Christopher; McKenzie, David R; Suchowerska, Natalka
2016-05-08
Flattening filter-free (FFF) beams are becoming the preferred beam type for stereotactic radiosurgery (SRS) and stereotactic ablative radiation therapy (SABR), as they enable an increase in dose rate and a decrease in treatment time. This work assesses the effects of the flattening filter on small field output factors for 6 MV beams generated by both Elekta and Varian linear accelerators, and determines differences between detector response in flattened (FF) and FFF beams. Relative output factors were measured with a range of detectors (diodes, ionization cham-bers, radiochromic film, and microDiamond) and referenced to the relative output factors measured with an air core fiber optic dosimeter (FOD), a scintillation dosimeter developed at Chris O'Brien Lifehouse, Sydney. Small field correction factors were generated for both FF and FFF beams. Diode measured detector response was compared with a recently published mathematical relation to predict diode response corrections in small fields. The effect of flattening filter removal on detector response was quantified using a ratio of relative detector responses in FFF and FF fields for the same field size. The removal of the flattening filter was found to have a small but measurable effect on ionization chamber response with maximum deviations of less than ± 0.9% across all field sizes measured. Solid-state detectors showed an increased dependence on the flattening filter of up to ± 1.6%. Measured diode response was within ± 1.1% of the published mathematical relation for all fields up to 30 mm, independent of linac type and presence or absence of a flattening filter. For 6 MV beams, detector correction factors between FFF and FF beams are interchangeable for a linac between FF and FFF modes, providing that an additional uncertainty of up to ± 1.6% is accepted.
1987-12-01
FIR filter can be described in the following. [Ref. 2] 1. FIR filters with exact linear phase can be easily designed. Linear phase filters are important...response for the four cases of linear phase filter , i.e., even or odd symmetry with an even or odd number of terms, can be written in the form: H (eJ ) = e...Ansari, The Design and Application of Optimal FIR Fractional Phase Filters , IEEE on Acoutics, Speech and Signal Processing, Vol. 2, 1987, pp.896-899. 77 14
A Low Cost Structurally Optimized Design for Diverse Filter Types
Kazmi, Majida; Aziz, Arshad; AKHTAR, Pervez; Ikram, Nassar
2016-01-01
A wide range of image processing applications deploys two dimensional (2D)-filters for performing diversified tasks such as image enhancement, edge detection, noise suppression, multi scale decomposition and compression etc. All of these tasks require multiple type of 2D-filters simultaneously to acquire the desired results. The resource hungry conventional approach is not a viable option for implementing these computationally intensive 2D-filters especially in a resource constraint environme...
Optimizing Biorefinery Design and Operations via Linear Programming Models
Energy Technology Data Exchange (ETDEWEB)
Talmadge, Michael; Batan, Liaw; Lamers, Patrick; Hartley, Damon; Biddy, Mary; Tao, Ling; Tan, Eric
2017-03-28
The ability to assess and optimize economics of biomass resource utilization for the production of fuels, chemicals and power is essential for the ultimate success of a bioenergy industry. The team of authors, consisting of members from the National Renewable Energy Laboratory (NREL) and the Idaho National Laboratory (INL), has developed simple biorefinery linear programming (LP) models to enable the optimization of theoretical or existing biorefineries. The goal of this analysis is to demonstrate how such models can benefit the developing biorefining industry. It focuses on a theoretical multi-pathway, thermochemical biorefinery configuration and demonstrates how the biorefinery can use LP models for operations planning and optimization in comparable ways to the petroleum refining industry. Using LP modeling tools developed under U.S. Department of Energy's Bioenergy Technologies Office (DOE-BETO) funded efforts, the authors investigate optimization challenges for the theoretical biorefineries such as (1) optimal feedstock slate based on available biomass and prices, (2) breakeven price analysis for available feedstocks, (3) impact analysis for changes in feedstock costs and product prices, (4) optimal biorefinery operations during unit shutdowns / turnarounds, and (5) incentives for increased processing capacity. These biorefinery examples are comparable to crude oil purchasing and operational optimization studies that petroleum refiners perform routinely using LPs and other optimization models. It is important to note that the analyses presented in this article are strictly theoretical and they are not based on current energy market prices. The pricing structure assigned for this demonstrative analysis is consistent with $4 per gallon gasoline, which clearly assumes an economic environment that would favor the construction and operation of biorefineries. The analysis approach and examples provide valuable insights into the usefulness of analysis tools for
Singh, R.; Verma, H. K.
2013-12-01
This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.
Institute of Scientific and Technical Information of China (English)
Li Shu; Zhuo Jiashou; Ren Qingwen
2000-01-01
In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.
Noise assisted excitation energy transfer in a linear model of a selectivity filter backbone strand
Bassereh, Hassan; Salari, Vahid; Shahbazi, Farhad
2015-07-01
In this paper, we investigate the effect of noise and disorder on the efficiency of excitation energy transfer (EET) in a N=5 sites linear chain with ‘static’ dipole-dipole couplings. In fact, here, the disordered chain is a toy model for one strand of the selectivity filter backbone in ion channels. It has recently been discussed that the presence of quantum coherence in the selectivity filter is possible and can play a role in mediating ion-conduction and ion-selectivity in the selectivity filter. The question is ‘how a quantum coherence can be effective in such structures while the environment of the channel is dephasing (i.e. noisy)?’ Basically, we expect that the presence of the noise should have a destructive effect in the quantum transport. In fact, we show that such expectation is valid for ordered chains. However, our results indicate that introducing the dephasing in the disordered chains leads to the weakening of the localization effects, arising from the multiple back-scatterings due to the randomness, and then increases the efficiency of quantum energy transfer. Thus, the presence of noise is crucial for the enhancement of EET efficiency in disordered chains. We also show that the contribution of both classical and quantum mechanical effects are required to improve the speed of energy transfer along the chain. Our analysis may help for better understanding of fast and efficient functioning of the selectivity filters in ion channels.
Noise assisted excitation energy transfer in a linear model of a selectivity filter backbone strand.
Bassereh, Hassan; Salari, Vahid; Shahbazi, Farhad
2015-07-15
In this paper, we investigate the effect of noise and disorder on the efficiency of excitation energy transfer (EET) in a N = 5 sites linear chain with 'static' dipole-dipole couplings. In fact, here, the disordered chain is a toy model for one strand of the selectivity filter backbone in ion channels. It has recently been discussed that the presence of quantum coherence in the selectivity filter is possible and can play a role in mediating ion-conduction and ion-selectivity in the selectivity filter. The question is 'how a quantum coherence can be effective in such structures while the environment of the channel is dephasing (i.e. noisy)?' Basically, we expect that the presence of the noise should have a destructive effect in the quantum transport. In fact, we show that such expectation is valid for ordered chains. However, our results indicate that introducing the dephasing in the disordered chains leads to the weakening of the localization effects, arising from the multiple back-scatterings due to the randomness, and then increases the efficiency of quantum energy transfer. Thus, the presence of noise is crucial for the enhancement of EET efficiency in disordered chains. We also show that the contribution of both classical and quantum mechanical effects are required to improve the speed of energy transfer along the chain. Our analysis may help for better understanding of fast and efficient functioning of the selectivity filters in ion channels.
OPTIMAL THICKNESS OF A CYLINDRICAL SHELL - AN OPTIMAL CONTROL PROBLEM IN LINEAR ELASTICITY THEORY
Directory of Open Access Journals (Sweden)
Peter Nestler
2013-01-01
Full Text Available In this paper we discuss optimization problems for cylindrical tubeswhich are loaded by an applied force. This is a problem of optimal control in linear elasticity theory (shape optimization. We are looking for an optimal thickness minimizing the deflection (deformation of the tube under the influence of an external force. From basic equations of mechanics, we derive the equation of deformation. We apply the displacement approach from shell theory and make use of the hypotheses of Mindlin and Reissner. A corresponding optimal control problem is formulated and first order necessary conditions for the optimal solution (optimal thickness are derived. We present numerical examples which were solved by the finite element method.
Optimal Piecewise Linear Basis Functions in Two Dimensions
Energy Technology Data Exchange (ETDEWEB)
Brooks III, E D; Szoke, A
2009-01-26
We use a variational approach to optimize the center point coefficients associated with the piecewise linear basis functions introduced by Stone and Adams [1], for polygonal zones in two Cartesian dimensions. Our strategy provides optimal center point coefficients, as a function of the location of the center point, by minimizing the error induced when the basis function interpolation is used for the solution of the time independent diffusion equation within the polygonal zone. By using optimal center point coefficients, one expects to minimize the errors that occur when these basis functions are used to discretize diffusion equations, or transport equations in optically thick zones (where they approach the solution of the diffusion equation). Our optimal center point coefficients satisfy the requirements placed upon the basis functions for any location of the center point. We also find that the location of the center point can be optimized, but this requires numerical calculations. Curiously, the optimum center point location is independent of the values of the dependent variable on the corners only for quadrilaterals.
Directory of Open Access Journals (Sweden)
Carlos Pozo
Full Text Available Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study
Pozo, Carlos; Guillén-Gosálbez, Gonzalo; Sorribas, Albert; Jiménez, Laureano
2012-01-01
Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the
Daugman, J G
1985-07-01
Two-dimensional spatial linear filters are constrained by general uncertainty relations that limit their attainable information resolution for orientation, spatial frequency, and two-dimensional (2D) spatial position. The theoretical lower limit for the joint entropy, or uncertainty, of these variables is achieved by an optimal 2D filter family whose spatial weighting functions are generated by exponentiated bivariate second-order polynomials with complex coefficients, the elliptic generalization of the one-dimensional elementary functions proposed in Gabor's famous theory of communication [J. Inst. Electr. Eng. 93, 429 (1946)]. The set includes filters with various orientation bandwidths, spatial-frequency bandwidths, and spatial dimensions, favoring the extraction of various kinds of information from an image. Each such filter occupies an irreducible quantal volume (corresponding to an independent datum) in a four-dimensional information hyperspace whose axes are interpretable as 2D visual space, orientation, and spatial frequency, and thus such a filter set could subserve an optimally efficient sampling of these variables. Evidence is presented that the 2D receptive-field profiles of simple cells in mammalian visual cortex are well described by members of this optimal 2D filter family, and thus such visual neurons could be said to optimize the general uncertainty relations for joint 2D-spatial-2D-spectral information resolution. The variety of their receptive-field dimensions and orientation and spatial-frequency bandwidths, and the correlations among these, reveal several underlying constraints, particularly in width/length aspect ratio and principal axis organization, suggesting a polar division of labor in occupying the quantal volumes of information hyperspace.(ABSTRACT TRUNCATED AT 250 WORDS)
Panigrahi, Swapnesh; Ramachandran, Hema; Alouini, Mehdi
2016-01-01
The efficiency of using intensity modulated light for estimation of scattering properties of a turbid medium and for ballistic photon discrimination is theoretically quantified in this article. Using the diffusion model for modulated photon transport and considering a noisy quadrature demodulation scheme, the minimum-variance bounds on estimation of parameters of interest are analytically derived and analyzed. The existence of a variance-minimizing optimal modulation frequency is shown and its evolution with the properties of the intervening medium is derived and studied. Furthermore, a metric is defined to quantify the efficiency of ballistic photon filtering which may be sought when imaging through turbid media. The analytical derivation of this metric shows that the minimum modulation frequency required to attain significant ballistic discrimination depends only on the reduced scattering coefficient of the medium in a linear fashion for a highly scattering medium.
Panigrahi, Swapnesh; Fade, Julien; Ramachandran, Hema; Alouini, Mehdi
2016-07-11
The efficiency of using intensity modulated light for the estimation of scattering properties of a turbid medium and for ballistic photon discrimination is theoretically quantified in this article. Using the diffusion model for modulated photon transport and considering a noisy quadrature demodulation scheme, the minimum-variance bounds on estimation of parameters of interest are analytically derived and analyzed. The existence of a variance-minimizing optimal modulation frequency is shown and its evolution with the properties of the intervening medium is derived and studied. Furthermore, a metric is defined to quantify the efficiency of ballistic photon filtering which may be sought when imaging through turbid media. The analytical derivation of this metric shows that the minimum modulation frequency required to attain significant ballistic discrimination depends only on the reduced scattering coefficient of the medium in a linear fashion for a highly scattering medium.
Behavioral model for common mode filter and performance optimization aspects
Roc'h, A.; Bergsma, H.; Bergsma, J.G.; Leferink, Frank Bernardus Johannes
2008-01-01
A well designed common mode filter for motor drive application can significantly improve the level of electromagnetic interference generated by the cable and the motor housing. The subsequent design of this filter is strongly dependent on the actual in situ parameters of the motor drive and often
Sensor Fault Estimation Filter Design for Discrete-time Linear Time-varying Systems
Institute of Scientific and Technical Information of China (English)
WANG Zhen-Hua; RODRIGUES Mickael; THEILLIOL Didier; SHEN Yi
2014-01-01
This paper proposes a sensor fault diagnosis method for a class of discrete-time linear time-varying (LTV) systems. In this paper, the considered system is firstly formulated as a de-scriptor system representation by considering the sensor faults as auxiliary state variables. Based on the descriptor system model, a fault estimation filter which can simultaneously estimate the state and the sensor fault magnitudes is designed via a minimum-variance principle. Then, a fault diagnosis scheme is presented by using a bank of the proposed fault estimation filters. The novelty of this paper lies in developing a sensor fault diagnosis method for discrete LTV systems without any assumption on the dynamic of fault. Another advantage of the proposed method is its ability to detect, isolate and estimate sensor faults in the presence of process noise and measurement noise. Simulation results are given to illustrate the effectiveness of the proposed method.
Adaptive Command-Filtered Backstepping Control for Linear Induction Motor via Projection Algorithm
Directory of Open Access Journals (Sweden)
Wenxu Yan
2016-01-01
Full Text Available A theoretical framework of the position control for linear induction motors (LIM has been proposed. First, indirect field-oriented control of LIM is described. Then, the backstepping approach is used to ensure the convergence and robustness of the proposed control scheme against the external time-varying disturbances via Lyapunov stability theory. At the same time, in order to solve the differential expansion and the control saturation problems in the traditional backstepping, command filter is designed in the control and compensating signals are presented to eliminate the influence of the errors caused by command filters. Next, unknown total mass of the mover, viscous friction, and load disturbances are estimated by the projection-based adaptive law which bounds the estimated function and simultaneously guarantees the robustness of the proposed controller against the parameter uncertainties. Finally, simulation results are given to illustrate the validity and potential of the designed control scheme.
Decentralized Observer with a Consensus Filter for Distributed Discrete-Time Linear Systems
Acikmese, Behcet; Mandic, Milan
2011-01-01
This paper presents a decentralized observer with a consensus filter for the state observation of a discrete-time linear distributed systems. In this setup, each agent in the distributed system has an observer with a model of the plant that utilizes the set of locally available measurements, which may not make the full plant state detectable. This lack of detectability is overcome by utilizing a consensus filter that blends the state estimate of each agent with its neighbors' estimates. We assume that the communication graph is connected for all times as well as the sensing graph. It is proven that the state estimates of the proposed observer asymptotically converge to the actual plant states under arbitrarily changing, but connected, communication and sensing topologies. As a byproduct of this research, we also obtained a result on the location of eigenvalues, the spectrum, of the Laplacian for a family of graphs with self-loops.
Optease vena cava filter optimal indwelling time and retrievability.
Rimon, Uri; Bensaid, Paul; Golan, Gil; Garniek, Alexander; Khaitovich, Boris; Dotan, Zohar; Konen, Eli
2011-06-01
The purpose of this study was to assess the indwelling time and retrievability of the Optease IVC filter. Between 2002 and 2009, a total of 811 Optease filters were inserted: 382 for prophylaxis in multitrauma patients and 429 for patients with venous thromboembolic (VTE) disease. In 139 patients [97 men and 42 women; mean age, 36 (range, 17-82) years], filter retrieval was attempted. They were divided into two groups to compare change in retrieval policy during the years: group A, 60 patients with filter retrievals performed before December 31 2006; and group B, 79 patients with filter retrievals from January 2007 to October 2009. A total of 128 filters were successfully removed (57 in group A, and 71 in group B). The mean filter indwelling time in the study group was 25 (range, 3-122) days. In group A the mean indwelling time was 18 (range, 7-55) days and in group B 31 days (range, 8-122). There were 11 retrieval failures: 4 for inability to engage the filter hook and 7 for inability to sheathe the filter due to intimal overgrowth. The mean indwelling time of group A retrieval failures was 16 (range, 15-18) days and in group B 54 (range, 17-122) days. Mean fluoroscopy time for successful retrieval was 3.5 (range, 1-16.6) min and for retrieval failures 25.2 (range, 7.2-62) min. Attempts to retrieve the Optease filter can be performed up to 60 days, but more failures will be encountered with this approach.
Optimization of the reconstruction and anti-aliasing filter in a Wiener filter system
Wesselink, J.M.; Berkhoff, A.P.
2006-01-01
This paper discusses the influence of the reconstruction and anti-aliasing filters on the performance of a digital implementation of a Wiener filter for active noise control. The overall impact will be studied in combination with a multi-rate system approach. A reconstruction and anti-aliasing filte
DEFF Research Database (Denmark)
Lee, Carson Odell; Wagner, Florian Benedikt; Boe-Hansen, Rasmus
Nitrification is an important biological process commonly used in biological drinking water filters to remove ammonium from drinking water. Recent research has shown that a lack of micronutrients could be limiting the performance of these filters. Because nitrification is a biological process, ca...... to be an important diagnostic tool that could decrease regulatory hurdles, and save time and money....
Optimization of the reconstruction and anti-aliasing filter in a wiener filter system
Wesselink, J.M.; Berkhoff, A.P.
2006-01-01
This paper discusses the influence of the reconstruction and anti-aliasing filters on the performance of a digital implementation of a Wiener filter for active noise control. The overall impact will be studied in combination with a multi-rate system approach. A reconstruction and anti-aliasing filte
Power Saving Optimization for Linear Collider Interaction Region Parameters
Energy Technology Data Exchange (ETDEWEB)
Seryi, Andrei; /SLAC
2009-10-30
Optimization of Interaction Region parameters of a TeV energy scale linear collider has to take into account constraints defined by phenomena such as beam-beam focusing forces, beamstrahlung radiation, and hour-glass effect. With those constraints, achieving a desired luminosity of about 2E34 would require use of e{sup +}e{sup -} beams with about 10 MW average power. Application of the 'travelling focus' regime may allow the required beam power to be reduced by at least a factor of two, helping reduce the cost of the collider, while keeping the beamstrahlung energy loss reasonably low. The technique is illustrated for the 500 GeV CM parameters of the International Linear Collider. This technique may also in principle allow recycling the e{sup +}e{sup -} beams and/or recuperation of their energy.
Evolutionary pattern search algorithms for unconstrained and linearly constrained optimization
Energy Technology Data Exchange (ETDEWEB)
HART,WILLIAM E.
2000-06-01
The authors describe a convergence theory for evolutionary pattern search algorithms (EPSAs) on a broad class of unconstrained and linearly constrained problems. EPSAs adaptively modify the step size of the mutation operator in response to the success of previous optimization steps. The design of EPSAs is inspired by recent analyses of pattern search methods. The analysis significantly extends the previous convergence theory for EPSAs. The analysis applies to a broader class of EPSAs,and it applies to problems that are nonsmooth, have unbounded objective functions, and which are linearly constrained. Further, they describe a modest change to the algorithmic framework of EPSAs for which a non-probabilistic convergence theory applies. These analyses are also noteworthy because they are considerably simpler than previous analyses of EPSAs.
Treatment vault shielding for a flattening filter-free medical linear accelerator
Energy Technology Data Exchange (ETDEWEB)
Kry, Stephen F; Howell, Rebecca M; Polf, Jerimy; Mohan, Radhe; Vassiliev, Oleg N [Department of Radiation Physics, University of Texas M. D. Anderson Cancer Center, Houston, TX (United States)], E-mail: sfkry@mdanderson.org
2009-03-07
The requirements for shielding a treatment vault with a Varian Clinac 2100 medical linear accelerator operated both with and without the flattening filter were assessed. Basic shielding parameters, such as primary beam tenth-value layers (TVLs), patient scatter fractions, and wall scatter fractions, were calculated using Monte Carlo simulations of 6, 10 and 18 MV beams. Relative integral target current requirements were determined from treatment planning studies of several disease sites with, and without, the flattening filter. The flattened beam shielding data were compared to data published in NCRP Report No. 151, and the unflattened beam shielding data were presented relative to the NCRP data. Finally, the shielding requirements for a typical treatment vault were determined for a single-energy (6 MV) linac and a dual-energy (6 MV/18 MV) linac. With the exception of large-angle patient scatter fractions and wall scatter fractions, the vault shielding parameters were reduced when the flattening filter was removed. Much of this reduction was consistent with the reduced average energy of the FFF beams. Primary beam TVLs were reduced by 12%, on average, and small-angle scatter fractions were reduced by up to 30%. Head leakage was markedly reduced because less integral target current was required to deliver the target dose. For the treatment vault examined in the current study, removal of the flattening filter reduced the required thickness of the primary and secondary barriers by 10-20%, corresponding to 18 m{sup 3} less concrete to shield the single-energy linac and 36 m{sup 3} less concrete to shield the dual-energy linac. Thus, a shielding advantage was found when the linac was operated without the flattening filter. This translates into a reduction in occupational exposure and/or the cost and space of shielding.
Optimized digital filtering techniques for radiation detection with HPGe detectors
Salathe, Marco; Kihm, Thomas
2016-02-01
This paper describes state-of-the-art digital filtering techniques that are part of GEANA, an automatic data analysis software used for the GERDA experiment. The discussed filters include a novel, nonlinear correction method for ballistic deficits, which is combined with one of three shaping filters: a pseudo-Gaussian, a modified trapezoidal, or a modified cusp filter. The performance of the filters is demonstrated with a 762 g Broad Energy Germanium (BEGe) detector, produced by Canberra, that measures γ-ray lines from radioactive sources in an energy range between 59.5 and 2614.5 keV. At 1332.5 keV, together with the ballistic deficit correction method, all filters produce a comparable energy resolution of ~1.61 keV FWHM. This value is superior to those measured by the manufacturer and those found in publications with detectors of a similar design and mass. At 59.5 keV, the modified cusp filter without a ballistic deficit correction produced the best result, with an energy resolution of 0.46 keV. It is observed that the loss in resolution by using a constant shaping time over the entire energy range is small when using the ballistic deficit correction method.
Non-linear theory of elasticity and optimal design
Ratner, LW
2003-01-01
In order to select an optimal structure among possible similar structures, one needs to compare the elastic behavior of the structures. A new criterion that describes elastic behavior is the rate of change of deformation. Using this criterion, the safe dimensions of a structure that are required by the stress distributed in a structure can be calculated. The new non-linear theory of elasticity allows one to determine the actual individual limit of elasticity/failure of a structure using a simple non-destructive method of measurement of deformation on the model of a structure while presently it
STOCHASTIC LINEAR QUADRATIC OPTIMAL CONTROL PROBLEMS WITH RANDOM COEFFICIENTS
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
This paper studies a stochastic linear quadratic optimal control problem (LQ problem, for short), for which the coefficients are allowed to be random and the cost functional is allowed to have a negative weight on the square of the control variable. The authors introduce the stochastic Riccati equation for the LQ problem. This is a backward SDE with a complicated nonlinearity and a singularity. The local solvability of such a backward SDE is established, which by no means is obvious. For the case of deterministic coefficients, some further discussions on the Riccati equations have been carried out. Finally, an illustrative example is presented.
Optimal linear detectors for nonorthogonal amplify-and-forward protocol
Ahmed, Qasim Zeeshan
2013-06-01
In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors. © 2013 IEEE.
Linear optimal control of continuous time chaotic systems.
Merat, Kaveh; Abbaszadeh Chekan, Jafar; Salarieh, Hassan; Alasty, Aria
2014-07-01
In this research study, chaos control of continuous time systems has been performed by using dynamic programming technique. In the first step by crossing the response orbits with a selected Poincare section and subsequently applying linear regression method, the continuous time system is converted to a discrete type. Then, by solving the Riccati equation a sub-optimal algorithm has been devised for the obtained discrete chaotic systems. In the next step, by implementing the acquired algorithm on the quantized continuous time system, the chaos has been suppressed in the Rossler and AFM systems as some case studies.
Designing Networks: A Mixed-Integer Linear Optimization Approach
Gounaris, Chrysanthos E; Kevrekidis, Ioannis G; Floudas, Christodoulos A
2015-01-01
Designing networks with specified collective properties is useful in a variety of application areas, enabling the study of how given properties affect the behavior of network models, the downscaling of empirical networks to workable sizes, and the analysis of network evolution. Despite the importance of the task, there currently exists a gap in our ability to systematically generate networks that adhere to theoretical guarantees for the given property specifications. In this paper, we propose the use of Mixed-Integer Linear Optimization modeling and solution methodologies to address this Network Generation Problem. We present a number of useful modeling techniques and apply them to mathematically express and constrain network properties in the context of an optimization formulation. We then develop complete formulations for the generation of networks that attain specified levels of connectivity, spread, assortativity and robustness, and we illustrate these via a number of computational case studies.
Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics
Directory of Open Access Journals (Sweden)
J. Petrzela
2012-04-01
Full Text Available This paper shows the influence of piecewise-linear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integrator-based synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided
Non-linear DSGE Models and The Central Difference Kalman Filter
DEFF Research Database (Denmark)
Andreasen, Martin Møller
solved up to third order. A Monte Carlo study shows that this QML estimator is basically unbiased and normally distributed infi…nite samples for DSGE models solved using a second order or a third order approximation. These results hold even when structural shocks are Gaussian, Laplace distributed......This paper introduces a Quasi Maximum Likelihood (QML) approach based on the Cen- tral Difference Kalman Filter (CDKF) to estimate non-linear DSGE models with potentially non-Gaussian shocks. We argue that this estimator can be expected to be consistent and asymptotically normal for DSGE models...
A Novel Magnetic Linear Encoder Designed by Using the Slant Multi-Phase Filtering Model
Institute of Scientific and Technical Information of China (English)
SHI Yu; XING Huai-Zhong; ZHANG Huai-Wu; LIU Ying-Li; JING Yu-Lan; ZHONG Zhi-Yong
2004-01-01
@@ A novel design model based on the slant multi-phase filtering model is presented. A magnetic linear encoder with sinusoidal output voltage waveform has been investigated, and the improved sinusoidal output waveform can be easily acquired. A minimum 6% of distortion factor, when the difference of slant phase is 2π/3, is observed. It is found that the Wheatstone bridge type sensor, made of NiFe(450A)/NiO(300A) bilayers deposited on Si (001)substrate, can enhance both output signal and thermal stability, and then can be widely used in the field of magneto-resistive sensor.
Optimization techniques for OpenCL-based linear algebra routines
Kozacik, Stephen; Fox, Paul; Humphrey, John; Kuller, Aryeh; Kelmelis, Eric; Prather, Dennis W.
2014-06-01
The OpenCL standard for general-purpose parallel programming allows a developer to target highly parallel computations towards graphics processing units (GPUs), CPUs, co-processing devices, and field programmable gate arrays (FPGAs). The computationally intense domains of linear algebra and image processing have shown significant speedups when implemented in the OpenCL environment. A major benefit of OpenCL is that a routine written for one device can be run across many different devices and architectures; however, a kernel optimized for one device may not exhibit high performance when executed on a different device. For this reason kernels must typically be hand-optimized for every target device family. Due to the large number of parameters that can affect performance, hand tuning for every possible device is impractical and often produces suboptimal results. For this work, we focused on optimizing the general matrix multiplication routine. General matrix multiplication is used as a building block for many linear algebra routines and often comprises a large portion of the run-time. Prior work has shown this routine to be a good candidate for high-performance implementation in OpenCL. We selected several candidate algorithms from the literature that are suitable for parameterization. We then developed parameterized kernels implementing these algorithms using only portable OpenCL features. Our implementation queries device information supplied by the OpenCL runtime and utilizes this as well as user input to generate a search space that satisfies device and algorithmic constraints. Preliminary results from our work confirm that optimizations are not portable from one device to the next, and show the benefits of automatic tuning. Using a standard set of tuning parameters seen in the literature for the NVIDIA Fermi architecture achieves a performance of 1.6 TFLOPS on an AMD 7970 device, while automatically tuning achieves a peak of 2.7 TFLOPS
Directory of Open Access Journals (Sweden)
Xiang Gao
2012-05-01
Full Text Available In order to process target tracking approximation with unknown motion state models beforehand in a two-dimensional field of binary proximity sensors, the algorithms based on cost functions of particle filters and near-linear curve simple optimization are proposed in this paper. Through moving target across detecting intersecting fields of sensor nodes sequentially, cost functions are introduced to solve target tracking approximation and velocity estimation which is not similar to traditional particle filters that rely on probabilistic assumptions about the motion states. Then a near-linear curve geometric approach is used to simplify and easily describe target trajectories that are below a certain error measure. Because there maybe some sensor nodes invalid in practice, so a fault-tolerant detection is applied to avoid the nodes’ reporting fault and also improve accuracy of tracking at the same time. The validity of our algorithms is demonstrated through simulation results.
Topology optimization of pulse shaping filters using the Hilbert transform envelope extraction
DEFF Research Database (Denmark)
Lazarov, Boyan Stefanov; Matzen, René; Elesin, Yuriy
2011-01-01
Time domain topology optimization is applied to design pulse shaping filters. The objective function depends on the pulse envelope, which is extracted by utilizing the Hilbert transform. The gradients with respect to the topology optimization variables are derived, and the optimization methodology...
A digital filter optimization method for low power digital wireless communication system
Tarumi, Kousuke; Tsujimoto, Taizo; Yasuura, Hiroto
2003-01-01
In this paper, we introduce a design method for a low power digital baseband processing circuit. In particular, we focus on a digital FIR(Finite Impulse Response) filter that is a part of the digital baseband processing. Because the digital filter contains large power consuming components, such as adders and multipliers. We propose a design method to reduce power consumption of the digital FIR filter circuit by optimizing bitwidth of inputs of the mutipliers and the adders. We found that the ...
Optimal Filter Estimation for Lucas-Kanade Optical Flow
Directory of Open Access Journals (Sweden)
Remus Brad
2012-09-01
Full Text Available Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filtering approach as a pre-processing step for the Lucas-Kanade pyramidal optical flow algorithm. Based on a study of different types of filtering methods and applied on the Iterative Refined Lucas-Kanade, we have concluded on the best filtering practice. As the Gaussian smoothing filter was selected, an empirical approach for the Gaussian variance estimation was introduced. Tested on the Middlebury image sequences, a correlation between the image intensity value and the standard deviation value of the Gaussian function was established. Finally, we have found that our selection method offers a better performance for the Lucas-Kanade optical flow algorithm.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Temporal filters and spatial filters are widely used in many areas of signal processing. A number of optimal design criteria to these problems are available in the literature. Various computational techniques are also presented to optimize these criteria chosen. There are many drawbacks in these methods. In this paper, we introduce a unified framework for optimal design of temporal and spatial filters. Most of the optimal design problems of FIR filters and beamformers are included in the framework. It is shown that all the design problems can be reformulated as convex optimization form as the second-order cone programming (SOCP) and solved efficiently via the well-established interior point methods. The main advantage of our SOCP approach as compared with earlier approaches is that it can include most of the existing methods as its special cases, which leads to more flexible designs. Furthermore, the SOCP approach can optimize multiple required performance measures, which is the drawback of earlier approaches. The SOCP approach is also developed to optimally design temporal and spatial two-dimensional filter and spatial matrix filter. Numerical results demonstrate the effectiveness of the proposed approach.
Optimal design and performance verification of a broadband waveguide filter using ANN-GA algorithm
Directory of Open Access Journals (Sweden)
Manidipa Nath
2013-09-01
Full Text Available In this work design and optimization of EBGstructure having multiple dielectric posts uniformly placed insidea rectangular waveguide is done to extract filter responses.Frequency response of BPF configuration using trained ANNmodel of multipost rectangular waveguide are studied andoptimized using GA. The geometrical and positional dimensionof post parameters are varied in accordance to the requirementof reflectance and transmittance of the filter.
New optimal design method for trap damping sections in grid-connected LCL filters
DEFF Research Database (Denmark)
Beres, Remus Narcis; Wang, Xiongfei; Blaabjerg, Frede;
2014-01-01
A straightforward method is proposed in this paper to optimally design the damping sections of the LCL or LCL plus trap filters. The proposed method simplifies the iterative design procedure of the overall filter while ensuring minimum resonance peaking and smaller capacitor than otherwise would ...
Penalized Ensemble Kalman Filters for High Dimensional Non-linear Systems
Hou, Elizabeth; Hero, Alfred O
2016-01-01
The ensemble Kalman filter (EnKF) is a data assimilation technique that uses an ensemble of models, updated with data, to track the time evolution of a non-linear system. It does so by using an empirical approximation to the well-known Kalman filter. Unfortunately, its performance suffers when the ensemble size is smaller than the state space, as is often the case for computationally burdensome models. This scenario means that the empirical estimate of the state covariance is not full rank and possibly quite noisy. To solve this problem in this high dimensional regime, a computationally fast and easy to implement algorithm called the penalized ensemble Kalman filter (PEnKF) is proposed. Under certain conditions, it can be proved that the PEnKF does not require more ensemble members than state dimensions in order to have good performance. Further, the proposed approach does not require special knowledge of the system such as is used by localization methods. These theoretical results are supported with superior...
High-Rate Data-Hiding Robust to Linear Filtering for Colored Hosts
Directory of Open Access Journals (Sweden)
Pérez-González Fernando
2009-01-01
Full Text Available The discrete Fourier transform-rational dither modulation (DFT-RDM has been proposed as a way to provide robustness to linear-time-invariant (LTI filtering for quantization-based watermarking systems. This scheme has been proven to provide high rates for white Gaussian hosts but those rates considerably decrease for nonwhite hosts. In this paper the theoretical analysis of DFT-RDM is generalized to colored Gaussian hosts supplied with an explanation of the performance degradation with respect to white Gaussian hosts. Moreover the characterization of the watermark-to-noise ratio in the frequency domain is shown as an useful tool to give a simple and intuitive measure of performance. Afterwards an extension of DFT-RDM is proposed to improve its performance for colored hosts without assuming any additional knowledge on the attack filter. Our analysis is validated by experiments and the results of several simulations for different attack filters confirm the performance improvement afforded by the whitening operation for both Gaussian colored hosts and audio tracks.
Shimozato, Tomohiro; Aoyama, Yuichi; Matsunaga, Takuma; Tabushi, Katsuyoshi
2017-01-01
This work investigated the dosimetric properties of a 10-MV photon beam emitted from a medical linear accelerator (linac) with no flattening filter (FF). The aim of this study is to analyze the radiation fluence and energy emitted from the flattening filter free (FFF) linac using Monte Carlo (MC) simulations. The FFF linac was created by removing the FF from a linac in clinical use. Measurements of the depth dose (DD) and the off-axis profile were performed using a three-dimensional water phantom with an ionization chamber. A MC simulation for a 10-MV photon beam from this FFF linac was performed using the BEAMnrc code. The off-axis profiles for the FFF linac exhibited a chevron-like distribution, and the dose outside the irradiation field was found to be lower for the FFF linac than for a linac with an FF (FF linac). The DD curves for the FFF linac included many contaminant electrons in the build-up region. Therefore, for clinical use, a metal filter is additionally required to reduce the effects of the electron contamination. The mean energy of the FFF linac was found to be lower than that of the FF linac owing to the absence of beam hardening caused by the FF.
A FILTER-TRUST-REGION METHOD FOR LC1 UNCONSTRAINED OPTIMIZATION AND ITS GLOBAL CONVERGENCE
Institute of Scientific and Technical Information of China (English)
Zhenghao Yang; Wenyu Sun; Chuangyin Dang
2008-01-01
In this paper we present a filter-trust-region algorithm for solving LC1 unconstrained optimization problems which uses the second Dini upper directional derivative.We establish the global convergence of the algorithm under reasonable assumptions.
A robust approach to optimal matched filter design in ultrasonic non-destructive evaluation (NDE)
Li, Minghui; Hayward, Gordon
2017-02-01
The matched filter was demonstrated to be a powerful yet efficient technique to enhance defect detection and imaging in ultrasonic non-destructive evaluation (NDE) of coarse grain materials, provided that the filter was properly designed and optimized. In the literature, in order to accurately approximate the defect echoes, the design utilized the real excitation signals, which made it time consuming and less straightforward to implement in practice. In this paper, we present a more robust and flexible approach to optimal matched filter design using the simulated excitation signals, and the control parameters are chosen and optimized based on the real scenario of array transducer, transmitter-receiver system response, and the test sample, as a result, the filter response is optimized and depends on the material characteristics. Experiments on industrial samples are conducted and the results confirm the great benefits of the method.
Optimal control of switched linear systems based on Migrant Particle Swarm Optimization algorithm
Xie, Fuqiang; Wang, Yongji; Zheng, Zongzhun; Li, Chuanfeng
2009-10-01
The optimal control problem for switched linear systems with internally forced switching has more constraints than with externally forced switching. Heavy computations and slow convergence in solving this problem is a major obstacle. In this paper we describe a new approach for solving this problem, which is called Migrant Particle Swarm Optimization (Migrant PSO). Imitating the behavior of a flock of migrant birds, the Migrant PSO applies naturally to both continuous and discrete spaces, in which definitive optimization algorithm and stochastic search method are combined. The efficacy of the proposed algorithm is illustrated via a numerical example.
Optimization of H sup - output in a magnetically filtered multicusp source
Energy Technology Data Exchange (ETDEWEB)
Hosoda, Masayuki; Tanebe, Tomoaki; Naitou, Hirosi; Fukumasa, Osamu (Yamaguchi Univ. (Japan))
1991-10-01
On optimization of the volume production type H{sup -} ion source, the effects of both the magnetic filter position and the plasma grid bias voltage for H{sup -} output have been investigated experimentally. It is found that the H{sup -} output can be enhanced by optimizing the magnetic filter position, or the bias voltage of plasma grid. It is also confirmed that these phenomena correlate strongly with the variations of plasma parameters in the extraction region. (author).
A New Interpolation Approach for Linearly Constrained Convex Optimization
Espinoza, Francisco
2012-08-01
In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard\\'s interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton\\'s method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.
Application of adaptive non-linear 2D and 3D postprocessing filters for reduced dose abdominal CT.
Borgen, Lars; Kalra, Mannudeep K; Laerum, Frode; Hachette, Isabelle W; Fredriksson, Carina H; Sandborg, Michael; Smedby, Orjan
2012-04-01
Abdominal computed tomography (CT) is a frequently performed imaging procedure, resulting in considerable radiation doses to the patient population. Postprocessing filters are one of several dose reduction measures that might help to reduce radiation doses without loss of image quality. To assess and compare the effect of two- and three-dimensional (2D, 3D) non-linear adaptive filters on reduced dose abdominal CT images. Two baseline abdominal CT image series with a volume computer tomography dose index (CTDI (vol)) of 12 mGy and 6 mGy were acquired for 12 patients. Reduced dose images were postprocessed with 2D and 3D filters. Six radiologists performed blinded randomized, side-by-side image quality assessments. Objective noise was measured. Data were analyzed using visual grading regression and mixed linear models. All image quality criteria were rated as superior for 3D filtered images compared to reduced dose baseline and 2D filtered images (P 0.05). There were no significant variations of objective noise between standard dose and 2D or 3D filtered images. The quality of 3D filtered reduced dose abdominal CT images is superior compared to reduced dose unfiltered and 2D filtered images. For patients with BMI < 30 kg/m(2), 3D filtered images are comparable to standard dose images.
Design Optimization of Diesel Particulate Filter Using CFD
Directory of Open Access Journals (Sweden)
Mr. Y. Rajasekhar Reddy
2015-12-01
Full Text Available The diesel particulate filter (DPF is a device designed to remove diesel particulate matter or soot from the exhaust gas of a diesel engine. A series of tests have been performed on a downscaled DPF prototype. This prototype had high filtration efficiency. Then the next step is to study the soot and ash handling capacity of DPF system and perform tests on a full-scale prototype. In order to move forward to the next step the functionality of the filter should be investigated. Moreover, a complete model of flow inside the filter can help parameter investigation on both downscale and full-scale prototype. Building up a CFD model using fluent which is capable to simulate the flow through all channels and porous media of the filter plates and tuning the pressure drop parameters for all steps of filtration from clean filter to dirty one are the main achievements of this project. CFD results have been tuned by using experimental data of filtration tests.
Asynchronous parallel generating set search for linearly-constrained optimization.
Energy Technology Data Exchange (ETDEWEB)
Kolda, Tamara G.; Griffin, Joshua; Lewis, Robert Michael
2007-04-01
We describe an asynchronous parallel derivative-free algorithm for linearly-constrained optimization. Generating set search (GSS) is the basis of ourmethod. At each iteration, a GSS algorithm computes a set of search directionsand corresponding trial points and then evaluates the objective function valueat each trial point. Asynchronous versions of the algorithm have been developedin the unconstrained and bound-constrained cases which allow the iterations tocontinue (and new trial points to be generated and evaluated) as soon as anyother trial point completes. This enables better utilization of parallel resourcesand a reduction in overall runtime, especially for problems where the objec-tive function takes minutes or hours to compute. For linearly-constrained GSS,the convergence theory requires that the set of search directions conform to the3 nearby boundary. The complexity of developing the asynchronous algorithm forthe linearly-constrained case has to do with maintaining a suitable set of searchdirections as the search progresses and is the focus of this research. We describeour implementation in detail, including how to avoid function evaluations bycaching function values and using approximate look-ups. We test our imple-mentation on every CUTEr test problem with general linear constraints and upto 1000 variables. Without tuning to individual problems, our implementationwas able to solve 95% of the test problems with 10 or fewer variables, 75%of the problems with 11-100 variables, and nearly half of the problems with100-1000 variables. To the best of our knowledge, these are the best resultsthat have ever been achieved with a derivative-free method. Our asynchronousparallel implementation is freely available as part of the APPSPACK software.4
Design of one-dimensional optical pulse-shaping filters by time-domain topology optimization
DEFF Research Database (Denmark)
Yang, Lirong; Lavrinenko, Andrei; Hvam, Jørn Märcher
2009-01-01
Time-domain topology optimization is used here to design optical pulse-shaping filters in Si/SiO2 thin-film systems. A novel envelope objective function as well as explicit penalization are used to adapt the optimization method to this unique class of design problems.......Time-domain topology optimization is used here to design optical pulse-shaping filters in Si/SiO2 thin-film systems. A novel envelope objective function as well as explicit penalization are used to adapt the optimization method to this unique class of design problems....
Energy Technology Data Exchange (ETDEWEB)
Leach, R.R.; Schultz, C.; Dowla, F.
1997-07-15
Development of a worldwide network to monitor seismic activity requires deployment of seismic sensors in areas which have not been well studied or may have from available recordings. Development and testing of detection and discrimination algorithms requires a robust representative set of calibrated seismic events for a given region. Utilizing events with poor signal-to-noise (SNR) can add significant numbers to usable data sets, but these events must first be adequately filtered. Source and path effects can make this a difficult task as filtering demands are highly varied as a function of distance, event magnitude, bearing, depth etc. For a given region, conventional methods of filter selection can be quite subjective and may require intensive analysis of many events. In addition, filter parameters are often overly generalized or contain complicated switching. We have developed a method to provide an optimized filter for any regional or teleseismically recorded event. Recorded seismic signals contain arrival energy which is localized in frequency and time. Localized temporal signals whose frequency content is different from the frequency content of the pre-arrival record are identified using rms power measurements. The method is based on the decomposition of a time series into a set of time series signals or scales. Each scale represents a time-frequency band with a constant Q. SNR is calculated for a pre-event noise window and for a window estimated to contain the arrival. Scales with high SNR are used to indicate the band pass limits for the optimized filter.The results offer a significant improvement in SNR particularly for low SNR events. Our method provides a straightforward, optimized filter which can be immediately applied to unknown regions as knowledge of the geophysical characteristics is not required. The filtered signals can be used to map the seismic frequency response of a region and may provide improvements in travel-time picking, bearing estimation
Filters in topology optimization based on Helmholtz‐type differential equations
DEFF Research Database (Denmark)
Lazarov, Boyan Stefanov; Sigmund, Ole
2011-01-01
The aim of this paper is to apply a Helmholtz‐type partial differential equation as an alternative to standard density filtering in topology optimization problems. Previously, this approach has been successfully applied as a sensitivity filter. The usual filtering techniques in topology optimizat......The aim of this paper is to apply a Helmholtz‐type partial differential equation as an alternative to standard density filtering in topology optimization problems. Previously, this approach has been successfully applied as a sensitivity filter. The usual filtering techniques in topology...... optimization require information about the neighbor cells, which is difficult to obtain for fine meshes or complex domains and geometries. The complexity of the problem increases further in parallel computing, when the design domain is decomposed into multiple non‐overlapping partitions. Obtaining information...... from the neighbor subdomains is an expensive operation. The proposed filter technique requires only mesh information necessary for the finite element discretization of the problem. The main idea is to define the filtered variable implicitly as a solution of a Helmholtz‐type differential equation...
Optimization of multiplexed holographic gratings in PQ-PMMA for spectral-spatial imaging filters.
Luo, Yuan; Gelsinger, Paul J; Barton, Jennifer K; Barbastathis, George; Kostuk, Raymond K
2008-03-15
Holographic gratings formed in thick phenanthrenquinone- (PQ-) doped poly(methyl methacrylate) (PMMA) can be made to have narrowband spectral and spatial transmittance filtering properties. We present the design and performance of angle-multiplexed holographic filters formed in PQ-PMMA at 488 nm and reconstructed with a LED operated at approximately 630 nm. The dark delay time between exposure and the preillumination exposure of the polymer prior to exposure of the holographic area are varied to optimize the diffraction efficiency of multiplexed holographic filters. The resultant holographic filters can enhance the performance of four-dimensional spatial-spectral imaging systems. The optimized filters are used to simultaneously sample spatial and spectral information at five different depths separated by 50 microm within biological tissue samples.
Robust C subroutines for non-linear optimization
DEFF Research Database (Denmark)
Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun
2004-01-01
This report presents a package of robust and easy-to-use C subroutines for solving unconstrained and constrained non-linear optimization problems. The intention is that the routines should use the currently best algorithms available. All routines have standardized calls, and the user does not have...... by changing 1 to 0. The present report is a new and updated version of a previous report NI-91-03 with the same title, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated from Fortran to C. The reason for writing the present report is that some...... of the C subroutines have been replaced by more effective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modi ed to some extent. For a description of the original Fortran subroutines see the report [17]. The software...
Rigatos, Gerasimos G
2016-06-01
It is proven that the model of the p53-mdm2 protein synthesis loop is a differentially flat one and using a diffeomorphism (change of state variables) that is proposed by differential flatness theory it is shown that the protein synthesis model can be transformed into the canonical (Brunovsky) form. This enables the design of a feedback control law that maintains the concentration of the p53 protein at the desirable levels. To estimate the non-measurable elements of the state vector describing the p53-mdm2 system dynamics, the derivative-free non-linear Kalman filter is used. Moreover, to compensate for modelling uncertainties and external disturbances that affect the p53-mdm2 system, the derivative-free non-linear Kalman filter is re-designed as a disturbance observer. The derivative-free non-linear Kalman filter consists of the Kalman filter recursion applied on the linearised equivalent of the protein synthesis model together with an inverse transformation based on differential flatness theory that enables to retrieve estimates for the state variables of the initial non-linear model. The proposed non-linear feedback control and perturbations compensation method for the p53-mdm2 system can result in more efficient chemotherapy schemes where the infusion of medication will be better administered.
Abe, Tomomi; Hashimoto, Shuji; Matsumoto, Mitsuharu
2010-02-01
epsilon-filter can reduce most kinds of noise from a single-channel noisy signal while preserving signals that vary drastically such as speech signals. It can reduce not only stationary noise but also nonstationary noise. However, it has some parameters whose values are set empirically. So far, there have been few studies to evaluate the appropriateness of the parameter settings for epsilon-filter. This paper employs the correlation coefficient of the filter output and the difference between the filter input and output as the evaluation function of the parameter setting. This paper also describes the algorithm to set the optimal parameter value of epsilon-filter automatically. To evaluate the adequateness of the obtained parameter, the mean absolute error is calculated. The experimental results show that the adequate parameter in epsilon-filter can be obtained automatically by using the proposed method.
Mahmudin, D.; Estu, T. T.; Fathnan, A. A.; Maulana, Y. Y.; Daud, P.; Sugandhi, G.; Wijayanto, Y. N.
2016-11-01
Optical filter is very important components in WDM network. MRR is a basic structure to design the optical filter because of easy to design for improving its performance. This paper discusses an innovative structure of the MRR, which is Triple Coupler Ring Resonators (TCRR) for optical filter applications. Values of width between bus and ring and values of radius of the ring in the structure TCRR were analyzed and optimized for several variations for obtaining coupling coefficient values. Therefore, wide Free Spectral Range (FSR) and high crosstalk suppression bandwidth can be obtained. As results, at the optimized width of gap of 100 nm and the optimized radiation of 8 μm, FSR of 2.85 THz and crosstalk suppression bandwidth of 60 GHz were achieved. Based on the results, this structure can be used for filtering optical signals in optical fiber communication.
Linear versus quadratic portfolio optimization model with transaction cost
Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah
2014-06-01
Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.
ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (CDC VERSION)
Armstrong, E. S.
1994-01-01
This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following
ORACLS- OPTIMAL REGULATOR ALGORITHMS FOR THE CONTROL OF LINEAR SYSTEMS (DEC VAX VERSION)
Frisch, H.
1994-01-01
This control theory design package, called Optimal Regulator Algorithms for the Control of Linear Systems (ORACLS), was developed to aid in the design of controllers and optimal filters for systems which can be modeled by linear, time-invariant differential and difference equations. Optimal linear quadratic regulator theory, currently referred to as the Linear-Quadratic-Gaussian (LQG) problem, has become the most widely accepted method of determining optimal control policy. Within this theory, the infinite duration time-invariant problems, which lead to constant gain feedback control laws and constant Kalman-Bucy filter gains for reconstruction of the system state, exhibit high tractability and potential ease of implementation. A variety of new and efficient methods in the field of numerical linear algebra have been combined into the ORACLS program, which provides for the solution to time-invariant continuous or discrete LQG problems. The ORACLS package is particularly attractive to the control system designer because it provides a rigorous tool for dealing with multi-input and multi-output dynamic systems in both continuous and discrete form. The ORACLS programming system is a collection of subroutines which can be used to formulate, manipulate, and solve various LQG design problems. The ORACLS program is constructed in a manner which permits the user to maintain considerable flexibility at each operational state. This flexibility is accomplished by providing primary operations, analysis of linear time-invariant systems, and control synthesis based on LQG methodology. The input-output routines handle the reading and writing of numerical matrices, printing heading information, and accumulating output information. The basic vector-matrix operations include addition, subtraction, multiplication, equation, norm construction, tracing, transposition, scaling, juxtaposition, and construction of null and identity matrices. The analysis routines provide for the following
Application of adaptive non-linear 2D and 3D postprocessing filters for reduced dose abdominal CT
Energy Technology Data Exchange (ETDEWEB)
Borgen, Lars (Dept. of Radiology, Drammen Hospital, Drammen and Buskerud Univ. College, Drammen (Norway)), Email: lars.borgen@vestreviken.no; Kalra, Mannudeep K. (Massachusetts General Hospital Imaging, Harvard Medical School, Massachusetts General Hospital, Boston (United States)); Laerum, Frode (Dept. of Radiology, Akershus Univ. Hospital, Loerenskog (Norway)); Hachette, Isabelle W.; Fredriksson, Carina H. (ContextVision AB, Linkoeping (Sweden)); Sandborg, Michael (Dept. of Medical Physics, IMH, Faculty of Health Sciences, Linkoeping Univ., County Council of Oestergoetland, Linkoeping (Sweden); Center for Medical Image Science and Visualization, Linkoeping (Sweden)); Smedby, Oerjan (Center for Medical Image Science and Visualization, Linkoeping (Sweden); Dept. of Radiology, Linkoeping Univ., Linkoeping (Sweden))
2012-04-15
Background: Abdominal computed tomography (CT) is a frequently performed imaging procedure, resulting in considerable radiation doses to the patient population. Postprocessing filters are one of several dose reduction measures that might help to reduce radiation doses without loss of image quality. Purpose: To assess and compare the effect of two- and three-dimensional (2D, 3D) non-linear adaptive filters on reduced dose abdominal CT images. Material and Methods: Two baseline abdominal CT image series with a volume computer tomography dose index (CTDI{sub vol}) of 12 mGy and 6 mGy were acquired for 12 patients. Reduced dose images were postprocessed with 2D and 3D filters. Six radiologists performed blinded randomized, side-by-side image quality assessments. Objective noise was measured. Data were analyzed using visual grading regression and mixed linear models. Results: All image quality criteria were rated as superior for 3D filtered images compared to reduced dose baseline and 2D filtered images (P < 0.01). Standard dose images had better image quality than reduced dose 3D filtered images (P < 0.01), but similar image noise. For patients with body mass index (BMI) < 30 kg/m2 however, 3D filtered images were rated significantly better than normal dose images for two image criteria (P < 0.05), while no significant difference was found for the remaining three image criteria (P > 0.05). There were no significant variations of objective noise between standard dose and 2D or 3D filtered images. Conclusion: The quality of 3D filtered reduced dose abdominal CT images is superior compared to reduced dose unfiltered and 2D filtered images. For patients with BMI < 30 kg/m2, 3D filtered images are comparable to standard dose images
Improved simple optimization (SOPT algorithm for unconstrained non-linear optimization problems
Directory of Open Access Journals (Sweden)
J. Thomas
2016-09-01
Full Text Available In the recent years, population based meta-heuristic are developed to solve non-linear optimization problems. These problems are difficult to solve using traditional methods. Simple optimization (SOPT algorithm is one of the simple and efficient meta-heuristic techniques to solve the non-linear optimization problems. In this paper, SOPT is compared with some of the well-known meta-heuristic techniques viz. Artificial Bee Colony algorithm (ABC, Particle Swarm Optimization (PSO, Genetic Algorithm (GA and Differential Evolutions (DE. For comparison, SOPT algorithm is coded in MATLAB and 25 standard test functions for unconstrained optimization having different characteristics are run for 30 times each. The results of experiments are compared with previously reported results of other algorithms. Promising and comparable results are obtained for most of the test problems. To improve the performance of SOPT, an improvement in the algorithm is proposed which helps it to come out of local optima when algorithm gets trapped in it. In almost all the test problems, improved SOPT is able to get the actual solution at least once in 30 runs.
Sukarno; Law, Cheryl Suwen; Santos, Abel
2017-06-08
We present the first realisation of linear variable bandpass filters in nanoporous anodic alumina (NAA-LVBPFs) photonic crystal structures. NAA gradient-index filters (NAA-GIFs) are produced by sinusoidal pulse anodisation and used as photonic crystal platforms to generate NAA-LVBPFs. The anodisation period of NAA-GIFs is modified from 650 to 850 s to systematically tune the characteristic photonic stopband of these photonic crystals across the UV-visible-NIR spectrum. Then, the nanoporous structure of NAA-GIFs is gradually widened along the surface under controlled conditions by wet chemical etching using a dip coating approach aiming to create NAA-LVBPFs with finely engineered optical properties. We demonstrate that the characteristic photonic stopband and the iridescent interferometric colour displayed by these photonic crystals can be tuned with precision across the surface of NAA-LVBPFs by adjusting the fabrication and etching conditions. Here, we envisage for the first time the combination of the anodisation period and etching conditions as a cost-competitive, facile, and versatile nanofabrication approach that enables the generation of a broad range of unique LVBPFs covering the spectral regions. These photonic crystal structures open new opportunities for multiple applications, including adaptive optics, hyperspectral imaging, fluorescence diagnostics, spectroscopy, and sensing.
The Optimization of a Microfluidic CTC Filtering Chip by Simulation
Huan Li; Jianfeng Chen; Wenqiang Du; Youjun Xia; Depei Wang; Gang Zhao; Jiaru Chu
2017-01-01
The detection and separation of circulating tumor cells (CTCs) are crucial in early cancer diagnosis and cancer prognosis. Filtration through a thin film is one of the size and deformability based separation methods, which can isolate rare CTCs from the peripheral blood of cancer patients regardless of their heterogeneity. In this paper, volume of fluid (VOF) multiphase flow models are employed to clarify the cells’ filtering processes. The cells may deform significantly when they enter a cha...
Tap-length optimization of adaptive filters used in stereophonic acoustic echo cancellation
DEFF Research Database (Denmark)
Kar, Asutosh; Swamy, M.N.S.
2017-01-01
of acoustic echo paths. The tap-length optimization is applied to a single long adaptive filter with thousands of coefficients to decrease the total number of weights, which in turn reduces the computational load. To further increase the convergence rate, the proposed tap-length-optimization algorithm...
Waffenschmidt, Siw; Hermanns, Tatjana; Gerber-Grote, Andreas; Mostardt, Sarah
2017-02-01
To determine a suitable approach to a systematic search for epidemiologic publications in bibliographic databases. For this purpose, suitable sensitive, precise, and optimized filters were to be selected for MEDLINE searches. In addition, the relevance of bibliographic databases was determined. Epidemiologic systematic reviews (SRs) retrieved in a systematic search and company dossiers were screened to identify epidemiologic publications (primary studies and SRs) published since 2007. These publications were used to generate a test and validation set. Furthermore, each SR's search strategy was reviewed, and epidemiologic filters were extracted. The search syntaxes were validated using the relative recall method. The test set comprises 729 relevant epidemiologic publications, of which 566 were MEDLINE-indexed. About 27 epidemiologic filters were extracted. One suitable sensitive filter was identified (Larney et al. 2013: 95.94% sensitivity). Precision was presumably underestimated so that no precise or optimized filters can be recommended. About 77.64% of the publications were found in MEDLINE. There is currently no suitable approach to conducting efficient systematic searches for epidemiologic publications in bibliographic databases. The filter by Larney et al. (2013) can be used for sensitive MEDLINE searches. No robust conclusions can be drawn on precise or optimized filters. Additional search approaches should be considered. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.
In-plane Material Filters for the Discrete Material Optimization Method
DEFF Research Database (Denmark)
Sørensen, Rene; Lund, Erik
2015-01-01
This paper presents in-plane material filters for the Discrete Material Optimization method used for optimizing laminated composite structures. The filters make it possible for engineers to specify a minimum length scale which governs the minimum size of areas with constant material continuity....... Consequently, engineers can target the available production methods, and thereby increase its manufacturability while the optimizer is free to determine which material to apply together with an optimum location, shape, and size of these areas with constant material continuity. By doing so, engineers no longer...... have to group elements together in so-called patches, so to statically impose a minimum length scale. The proposed method imposes the minimum length scale through a standard density filter known from topology optimization of isotropic materials. This minimum length scale is generally referred...
Two-Dimensional IIR Filter Design Using Simulated Annealing Based Particle Swarm Optimization
Directory of Open Access Journals (Sweden)
Supriya Dhabal
2014-01-01
Full Text Available We present a novel hybrid algorithm based on particle swarm optimization (PSO and simulated annealing (SA for the design of two-dimensional recursive digital filters. The proposed method, known as SA-PSO, integrates the global search ability of PSO with the local search ability of SA and offsets the weakness of each other. The acceptance criterion of Metropolis is included in the basic algorithm of PSO to increase the swarm’s diversity by accepting sometimes weaker solutions also. The experimental results reveal that the performance of the optimal filter designed by the proposed SA-PSO method is improved. Further, the convergence behavior as well as optimization accuracy of proposed method has been improved significantly and computational time is also reduced. In addition, the proposed SA-PSO method also produces the best optimal solution with lower mean and variance which indicates that the algorithm can be used more efficiently in realizing two-dimensional digital filters.
Optimal O(1 Bilateral Filter with Arbitrary Spatial and Range Kernels Using Sparse Approximation
Directory of Open Access Journals (Sweden)
Shengdong Pan
2014-01-01
Full Text Available A number of acceleration schemes for speeding up the time-consuming bilateral filter have been proposed in the literature. Among these techniques, the histogram-based bilateral filter trades the flexibility for achieving O(1 computational complexity using box spatial kernel. A recent study shows that this technique can be leveraged for O(1 bilateral filter with arbitrary spatial and range kernels by linearly combining the results of multiple-box bilateral filters. However, this method requires many box bilateral filters to obtain sufficient accuracy when approximating the bilateral filter with a large spatial kernel. In this paper, we propose approximating arbitrary spatial kernel using a fixed number of boxes. It turns out that the multiple-box spatial kernel can be applied in many O(1 acceleration schemes in addition to the histogram-based one. Experiments on the application to the histogram-based acceleration are presented in this paper. Results show that the proposed method has better accuracy in approximating the bilateral filter with Gaussian spatial kernel, compared with the previous histogram-based methods. Furthermore, the performance of the proposed histogram-based bilateral filter is robust with respect to the parameters of the filter kernel.
Geometry optimization of linear and annular plasma synthetic jet actuators
Neretti, G.; Seri, P.; Taglioli, M.; Shaw, A.; Iza, F.; Borghi, C. A.
2017-01-01
The electrohydrodynamic (EHD) interaction induced in atmospheric air pressure by a surface dielectric barrier discharge (DBD) actuator has been experimentally investigated. Plasma synthetic jet actuators (PSJAs) are DBD actuators able to induce an air stream perpendicular to the actuator surface. These devices can be used in the field of aerodynamics to prevent or induce flow separation, modify the laminar to turbulent transition inside the boundary layer, and stabilize or mix air flows. They can also be used to enhance indirect plasma treatment effects, increasing the reactive species delivery rate onto surfaces and liquids. This can play a major role in plasma processing and chemical kinetics modelling, where often only diffusive mechanisms are considered. This paper reports on the importance that different electrode geometries can have on the performance of different PSJAs. A series of DBD aerodynamic actuators designed to produce perpendicular jets has been fabricated on two-layer printed circuit boards (PCBs). Both linear and annular geometries were considered, testing different upper electrode distances in the linear case and different diameters in the annular one. An AC voltage supplied at a peak of 11.5 kV and a frequency of 5 kHz was used. Lower electrodes were connected to the ground and buried in epoxy resin to avoid undesired plasma generation on the lower actuator surface. Voltage and current measurements were carried out to evaluate the active power delivered to the discharges. Schlieren imaging allowed the induced jets to be visualized and gave an estimate of their evolution and geometry. Pitot tube measurements were performed to obtain the velocity profiles of the PSJAs and to estimate the mechanical power delivered to the fluid. The optimal values of the inter-electrode distance and diameter were found in order to maximize jet velocity, mechanical power or efficiency. Annular geometries were found to achieve the best performance.
Liang, Lili; Liu, Han
2013-12-01
Dual-tree transforms have recently received much attention for the properties of shift-invariance and directional-selectivity. However, their designs generally encounter fractional-delay constraints, and become more complicated for providing linear-phase (LP) individual filters and flexible directional-selectivity, two important properties in image processing. In this paper, we propose an alternative shift-invariant and directional-selective transform-the dual-tree cosine-modulated filter bank (DTCMFB). In the proposed DTCMFB, its primal and dual filter banks are derived by cosine-modulating one LP prototype filter, and thus its design involves no fractional-delay constraints. Meanwhile, the derived modulation technique guarantees each individual filter to be LP and the LP condition is satisfied without any constraint on the prototype filter. By separable operations, the DTCMFB is extended to two-dimensions. The resulting 2D DTCMFB can provide much more flexible directional-selectivity. Finally, several simulations are given to verify the proposed DTCMFB, and the experiments on nonlinear approximation and image denoising are presented to demonstrate its potential in image processing.
New hybrid genetic particle swarm optimization algorithm to design multi-zone binary filter.
Lin, Jie; Zhao, Hongyang; Ma, Yuan; Tan, Jiubin; Jin, Peng
2016-05-16
The binary phase filters have been used to achieve an optical needle with small lateral size. Designing a binary phase filter is still a scientific challenge in such fields. In this paper, a hybrid genetic particle swarm optimization (HGPSO) algorithm is proposed to design the binary phase filter. The HGPSO algorithm includes self-adaptive parameters, recombination and mutation operations that originated from the genetic algorithm. Based on the benchmark test, the HGPSO algorithm has achieved global optimization and fast convergence. In an easy-to-perform optimizing procedure, the iteration number of HGPSO is decreased to about a quarter of the original particle swarm optimization process. A multi-zone binary phase filter is designed by using the HGPSO. The long depth of focus and high resolution are achieved simultaneously, where the depth of focus and focal spot transverse size are 6.05λ and 0.41λ, respectively. Therefore, the proposed HGPSO can be applied to the optimization of filter with multiple parameters.
Lehtinen, B.; Geyser, L. C.
1984-01-01
AESOP is a computer program for use in designing feedback controls and state estimators for linear multivariable systems. AESOP is meant to be used in an interactive manner. Each design task that the program performs is assigned a "function" number. The user accesses these functions either (1) by inputting a list of desired function numbers or (2) by inputting a single function number. In the latter case the choice of the function will in general depend on the results obtained by the previously executed function. The most important of the AESOP functions are those that design,linear quadratic regulators and Kalman filters. The user interacts with the program when using these design functions by inputting design weighting parameters and by viewing graphic displays of designed system responses. Supporting functions are provided that obtain system transient and frequency responses, transfer functions, and covariance matrices. The program can also compute open-loop system information such as stability (eigenvalues), eigenvectors, controllability, and observability. The program is written in ANSI-66 FORTRAN for use on an IBM 3033 using TSS 370. Descriptions of all subroutines and results of two test cases are included in the appendixes.
Design of Maximally Flat FIR Filters Based on Explicit Formulas Combined with Optimization
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A maximally flat FIR filter design method based on explicit formulas combined with simulated annealing and random search was presented. Utilizing the explicit formulas to calculate the initial values, the finite-word-length FIR filter design problem was converted into optimization of the filter coefficients. An optimization method combined with local discrete random search and simulated annealing was proposed, with the result of optimum solution in the sense of Chebyshev approximation. The proposed method can simplify the design process of FIR filter and reduce the calculation burden. The simulation result indicates that the proposed method is superior to the traditional round off method and can reduce the value of the objective function to 41%-74%.
Automation of Optimized Gabor Filter Parameter Selection for Road Cracks Detection
Directory of Open Access Journals (Sweden)
Haris Ahmad Khan
2016-03-01
Full Text Available Automated systems for road crack detection are extremely important in road maintenance for vehicle safety and traveler’s comfort. Emerging cracks in roads need to be detected and accordingly repaired as early as possible to avoid further damage thus reducing rehabilitation cost. In this paper, a robust method for Gabor filter parameters optimization for automatic road crack detection is discussed. Gabor filter has been used in previous literature for similar applications. However, there is a need for automatic selection of optimized Gabor filter parameters due to variation in texture of roads and cracks. The problem of change of background, which in fact is road texture, is addressed through a learning process by using synthetic road crack generation for Gabor filter parameter tuning. Tuned parameters are then tested on real cracks and a thorough quantitative analysis is performed for performance evaluation.
AN ITERATIVE ALGORITHM FOR OPTIMAL DESIGN OF NON-FREQUENCY-SELECTIVE FIR DIGITAL FILTERS
Institute of Scientific and Technical Information of China (English)
Duan Miyi; Sun Chunlai; Liu Xin; Tian Xinguang
2008-01-01
This paper proposes a novel iterative algorithm for optimal design of non-frequency-se-lective Finite Impulse Response (FIR) digital filters based on the windowing method. Different from the traditional optimization concept of adjusting the window or the filter order in the windowing design of an FIR digital filter,the key idea of the algorithm is minimizing the approximation error by succes-sively modifying the design result through an iterative procedure under the condition of a fixed window length. In the iterative procedure,the known deviation of the designed frequency response in each iteration from the ideal frequency response is used as a reference for the next iteration. Because the approximation error can be specified variably,the algorithm is applicable for the design of FIR digital filters with different technical requirements in the frequency domain. A design example is employed to illustrate the efficiency of the algorithm.
Institute of Scientific and Technical Information of China (English)
Shuo Zhang,Yan Zhao,Min Li,; Jianhui Zhao
2015-01-01
The global y optimal recursive filtering problem is stu-died for a class of systems with random parameter matrices, stochastic nonlinearities, correlated noises and missing measure-ments. The stochastic nonlinearities are presented in the system model to reflect multiplicative random disturbances, and the addi-tive noises, process noise and measurement noise, are assumed to be one-step autocorrelated as wel as two-step cross-correlated. A series of random variables is introduced as the missing rates governing the intermittent measurement losses caused by un-favorable network conditions. The aim of the addressed filtering problem is to design an optimal recursive filter for the uncertain systems based on an innovation approach such that the filtering error is global y minimized at each sampling time. A numerical simulation example is provided to il ustrate the effectiveness and applicability of the proposed algorithm.
Comparative analysis of zero aliasing logarithmic mapped optimal trade-off correlation filter
Tehsin, Sara; Rehman, Saad; Bilal, Ahmed; Chaudry, Qaiser; Saeed, Omer; Abbas, Muhammad; Young, Rupert
2017-05-01
Correlation filters are a well established means for target recognition tasks. However, the unintentional effect of circular correlation has a negative influence on the performance of correlation filters as they are implemented in frequency domain. The effects of aliasing are minimized by introducing zero aliasing constraints in the template and test image. In this paper, the comparative analysis of logarithmic zero aliasing optimal trade off correlation filters has been carried out for different types of target distortions. The zero aliasing Maximum Average Correlation Height (MACH) filter has been identified as the best choice based on our research for achieving enhanced results in the presence of any type of variance which are discussed in results section. The reformulation of the MACH expressions with zero aliasing has been made to demonstrate the achievable enhancement to the logarithmic MACH filter in target detection applications.
Extracting a common pulse like signal from Time Serie using a non linear Kalman Filter
Gazeaux, J.; Batista, D.; Ammann, C.; Naveau, P.; Jégat, C.; Gao, C.
2009-04-01
To understand the nature and cause of natural climate variability, it is important to attribute past climate variations to particular forcing factors. In this work, our main focus is to introduce an automatic assimilation procedure to estimate the magnitude of strong but short-lived perturbations, such as large explosive volcanic eruptions, using climate/proxies time series. The extraction and decomposition procedure is run on real multivariate time series of sulfate from ice cores drilled at different sites in Greenland. The sulfate ejected by volcanoes is transported through the stratosphere towards the poles and deposited via sedimentation near the pole. Sulfate in Greenland is then a marker of huge volcanic eruptions which occur all over the world. Such pulse-like processes are highly non linear, as much in time as for their intensity. If they are not detected, such pulse-like signals of extreme and rare events can perturb an objective calculation of the trend. This work is then as much an estimation procedure for such signals, as a first step to estimate a posteriori trend in the time series. Our extraction algorithm handles multivariate time series with a common but unknown forcing. This statistical procedure is based on a multivariate multi-state space model and a non linear Kalman Filter. The non linearity is solved using the calculation of a twice conditional expectation and variance. It can provide an accurate estimate of the timing and duration of individual pulse-like events from a set of different series covering the same temporal space. It not only allows for a more objective estimation of its associated peak amplitude and the subsequent time evolution of the signal, but at the same time it provides a measure of confidence through the posterior probability for each pulse-like event. The flexibility, robustness and limitations of our approach are discussed by applying our method to simulated time series and to the Monte-Carlo method to test the
Optimal control for perfect state transfer in linear quantum memory
Nakao, Hideaki; Yamamoto, Naoki
2017-03-01
A quantum memory is a system that enables transfer, storage, and retrieval of optical quantum states by ON/OFF switching of the control signal in each stage of the memory. In particular, it is known that, for perfect transfer of a single-photon state, appropriate shaping of the input pulse is required. However, in general, such a desirable pulse shape has a complicated form, which would be hard to generate in practice. In this paper, for a wide class of linear quantum memory systems, we develop a method that reduces the complexity of the input pulse shape of a single photon while maintaining the perfect state transfer. The key idea is twofold; (i) the control signal is allowed to vary continuously in time to introduce an additional degree of freedom, and then (ii) an optimal control problem is formulated to design a simple-formed input pulse and the corresponding control signal. Numerical simulations are conducted for Λ-type atomic media and networked atomic ensembles, to show the effectiveness of the proposed method.
Optimal configurations of filter cavity in future gravitational-wave detectors
Khalili, Farit Ya
2010-01-01
Sensitivity of future laser interferometric gravitational-wave detectors can be improved using squeezed light with frequency-dependent squeeze angle and/or amplitude, which can be created using additional so-called filter cavities. Here we compare performances of several variants of this scheme, proposed during last years, assuming the case of a single relatively short (tens of meters) filter cavity suitable for implementation already during the life cycle of the second generation detectors, like Advanced LIGO. Using numerical optimization, we show that the phase filtering scheme proposed by Kimble et al [Phys.Rev.D 65, 022002 (2001)] looks as the best candidate for this scenario.
Design, optimization and fabrication of an optical mode filter for integrated optics.
Magnin, Vincent; Zegaoui, Malek; Harari, Joseph; François, Marc; Decoster, Didier
2009-04-27
We present the design, optimization, fabrication and characterization of an optical mode filter, which attenuates the snaking behavior of light caused by a lateral misalignment of the input optical fiber relative to an optical circuit. The mode filter is realized as a bottleneck section inserted in an optical waveguide in front of a branching element. It is designed with Bézier curves. Its effect, which depends on the optical state of polarization, is experimentally demonstrated by investigating the equilibrium of an optical splitter, which is greatly improved however only in TM mode. The measured optical losses induced by the filter are 0.28 dB.
Reliability-Oriented Optimization of the LC Filter Design of a Buck DC-DC Converter
DEFF Research Database (Denmark)
Liu, Yi; Huang, Meng; Wang, Huai
2017-01-01
Lifetime is an important performance factor in the reliable operation of power converters. However, the state-of-the-art LC filter design of a buck DC-DC converter is limited to the specifications of voltage and current ripples and constrains in power density and cost without reliability...... considerations. This paper proposes a method to optimize the design of the LC filters from a reliability perspective, besides other considerations. An enhanced model is derived to quantify the lifetime of the capacitor in the filter considering the electro-thermal stress on it. Furthermore, the influence...
Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement
Directory of Open Access Journals (Sweden)
Byungwoon Park
2017-02-01
Full Text Available The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS performance of the low-cost SF receivers comparable to that of DF receivers.
Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement
Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon
2017-01-01
The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers. PMID:28245584
Optimal Divergence-Free Hatch Filter for GNSS Single-Frequency Measurement.
Park, Byungwoon; Lim, Cheolsoon; Yun, Youngsun; Kim, Euiho; Kee, Changdon
2017-02-24
The Hatch filter is a code-smoothing technique that uses the variation of the carrier phase. It can effectively reduce the noise of a pseudo-range with a very simple filter construction, but it occasionally causes an ionosphere-induced error for low-lying satellites. Herein, we propose an optimal single-frequency (SF) divergence-free Hatch filter that uses a satellite-based augmentation system (SBAS) message to reduce the ionospheric divergence and applies the optimal smoothing constant for its smoothing window width. According to the data-processing results, the overall performance of the proposed filter is comparable to that of the dual frequency (DF) divergence-free Hatch filter. Moreover, it can reduce the horizontal error of 57 cm to 37 cm and improve the vertical accuracy of the conventional Hatch filter by 25%. Considering that SF receivers dominate the global navigation satellite system (GNSS) market and that most of these receivers include the SBAS function, the filter suggested in this paper is of great value in that it can make the differential GPS (DGPS) performance of the low-cost SF receivers comparable to that of DF receivers.
Institute of Scientific and Technical Information of China (English)
ZHANG DE-TAO
2009-01-01
In this paper, we use the solutions of forward-backward stochastic differential equations to get the optimal control for backward stochastic linear quadratic optimal control problem. And we also give the linear feedback regulator for the optimal control problem by using the solutions of a group of Riccati equations.
Optimal design study of high order FIR digital filters based on neural network algorithm
Institute of Scientific and Technical Information of China (English)
王小华; 何怡刚
2004-01-01
An optimal design approach of high order FIR digital filter is developed based on the algorithm of neural networks with cosine basis function . The main idea is to minimize the sum of the square errors between the amplitude response of the desired FIR filter and that of the designed by training the weights of neural networks, then obtains the impulse response of FIR digital filter . The convergence theorem of the neural networks algorithm is presented and proved,and the optimal design method is introduced by designing four kinds of FIR digital filters , i.e., low-pass, high-pass,bandpass , and band-stop FIR digital filter. The results of the amplitude responses show that attenuation in stop-bands is more than 60 dB with no ripple and pulse existing in pass-bands, and cutoff frequency of passband and stop-band is easily controlled precisely . The presented optimal design approach of high order FIR digital filter is significantly effective.
FPGA Implementation of Optimal Filtering Algorithm for TileCal ROD System
Torres, J; Castillo, V; Cuenca, C; Ferrer, A; Fullana, E; González, V; Higón, E; Poveda, J; Ruiz-Martinez, A; Salvachúa, B; Sanchis, E; Solans, C; Valero, A; Valls, J A
2008-01-01
Traditionally, Optimal Filtering Algorithm has been implemented using general purpose programmable DSP chips. Alternatively, new FPGAs provide a highly adaptable and flexible system to develop this algorithm. TileCal ROD is a multi-channel system, where similar data arrives at very high sampling rates and is subject to simultaneous tasks. It include different FPGAs with high I/O and with parallel structures that provide a benefit at a data analysis. The Optical Multiplexer Board is one of the elements presents in TileCal ROD System. It has FPGAs devices that present an ideal platform for implementing Optimal Filtering Algorithm. Actually this algorithm is performing in the DSPs included at ROD Motherboard. This work presents an alternative to implement Optimal Filtering Algorithm.
Inverse Problem of Air Filtration of Nanoparticles: Optimal Quality Factors of Fibrous Filters
Directory of Open Access Journals (Sweden)
Dahua Shou
2015-01-01
Full Text Available Application of nanofibers has become an emerging approach to enhance filtration efficiency, but questions arise about the decrease in Quality factor (QF for certain particles due to the rapidly increasing pressure drop. In this paper, we theoretically investigate the QF of dual-layer filters for filtration of monodisperse and polydisperse nanoparticles. The inverse problem of air filtration, as defined in this work, consists in determining the optimal construction of the two-layer fibrous filter with the maximum QF. In comparison to a single-layer substrate, improved QF values for dual-layer filters are found when a second layer with proper structural parameters is added. The influences of solidity, fiber diameter, filter thickness, face velocity, and particle size on the optimization of QF are studied. The maximum QF values for realistic polydisperse particles with a lognormal size distribution are also found. Furthermore, we propose a modified QF (MQF accounting for the effects of energy cost and flow velocity, which are significant in certain operations. The optimal MQF of the dual-layer filter is found to be over twice that of the first layer. This work provides a quick tool for designing and optimizing fibrous structures with better performance for the air filtration of specific nanoparticles.
Optimal fractional delay-IIR filter design using cuckoo search algorithm.
Kumar, Manjeet; Rawat, Tarun Kumar
2015-11-01
This paper applied a novel global meta-heuristic optimization algorithm, cuckoo search algorithm (CSA) to determine optimal coefficients of a fractional delay-infinite impulse response (FD-IIR) filter and trying to meet the ideal frequency response characteristics. Since fractional delay-IIR filter design is a multi-modal optimization problem, it cannot be computed efficiently using conventional gradient based optimization techniques. A weighted least square (WLS) based fitness function is used to improve the performance to a great extent. FD-IIR filters of different orders have been designed using the CSA. The simulation results of the proposed CSA based approach have been compared to those of well accepted evolutionary algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The performance of the CSA based FD-IIR filter is superior to those obtained by GA and PSO. The simulation and statistical results affirm that the proposed approach using CSA outperforms GA and PSO, not only in the convergence rate but also in optimal performance of the designed FD-IIR filter (i.e., smaller magnitude error, smaller phase error, higher percentage improvement in magnitude and phase error, fast convergence rate). The absolute magnitude and phase error obtained for the designed 5th order FD-IIR filter are as low as 0.0037 and 0.0046, respectively. The percentage improvement in magnitude error for CSA based 5th order FD-IIR design with respect to GA and PSO are 80.93% and 74.83% respectively, and phase error are 76.04% and 71.25%, respectively.
Optimization of In-Cylinder Pressure Filter for Engine Research
2017-06-01
min, pmi = 9 bar) |Δp| (Short therm drift) [bar] ɘ.5 |Δpmi| [%] ɚ |Δpmax| [%] ə Insulation resistance at 23 °C [ Ohm ] >10^13 Shock resistance [g...Output resistance [ Ohm ] 10 Supply (amplifier) [VDC] 18 … 30 Zero setting (at 25°C, 1 bara) [mV] <±100 Linearity and hysteresis [% FSO ] <±1 Thermal
An OTA-C filter for ECG acquisition systems with highly linear range and less passband attenuation
Jihai, Duan; Chuang, Lan; Weilin, Xu; Baolin, Wei
2015-05-01
A fifth order operational transconductance amplifier-C (OTA-C) Butterworth type low-pass filter with highly linear range and less passband attenuation is presented for wearable bio-telemetry monitoring applications in a UWB wireless body area network. The source degeneration structure applied in typical small transconductance circuit is improved to provide a highly linear range for the OTA-C filter. Moreover, to reduce the passband attenuation of the filter, a cascode structure is employed as the output stage of the OTA. The OTA-based circuit is operated in weak inversion due to strict power limitation in the biomedical chip. The filter is fabricated in a SMIC 0.18-μm CMOS process. The measured results for the filter have shown a passband gain of -6.2 dB, while the -3-dB frequency is around 276 Hz. For the 0.8 VPP sinusoidal input at 100 Hz, a total harmonic distortion (THD) of -56.8 dB is obtained. An electrocardiogram signal with noise interference is fed into this chip to validate the function of the designed filter. Project supported by the National Natural Science Foundation of China (Nos. 61161003, 61264001, 61166004) and the Guangxi Natural Science Foundation (No. 2013GXNSFAA019333).
A Single Linear Prediction Filter that Accurately Predicts the AL Index
McPherron, R. L.; Chu, X.
2015-12-01
The AL index is a measure of the strength of the westward electrojet flowing along the auroral oval. It has two components: one from the global DP-2 current system and a second from the DP-1 current that is more localized near midnight. It is generally believed that the index a very poor measure of these currents because of its dependence on the distance of stations from the source of the two currents. In fact over season and solar cycle the coupling strength defined as the steady state ratio of the output AL to the input coupling function varies by a factor of four. There are four factors that lead to this variation. First is the equinoctial effect that modulates coupling strength with peaks (strongest coupling) at the equinoxes. Second is the saturation of the polar cap potential which decreases coupling strength as the strength of the driver increases. Since saturation occurs more frequently at solar maximum we obtain the result that maximum coupling strength occurs at equinox at solar minimum. A third factor is ionospheric conductivity with stronger coupling at summer solstice as compared to winter. The fourth factor is the definition of a solar wind coupling function appropriate to a given index. We have developed an optimum coupling function depending on solar wind speed, density, transverse magnetic field, and IMF clock angle which is better than previous functions. Using this we have determined the seasonal variation of coupling strength and developed an inverse function that modulates the optimum coupling function so that all seasonal variation is removed. In a similar manner we have determined the dependence of coupling strength on solar wind driver strength. The inverse of this function is used to scale a linear prediction filter thus eliminating the dependence on driver strength. Our result is a single linear filter that is adjusted in a nonlinear manner by driver strength and an optimum coupling function that is seasonal modulated. Together this
Wang, Xiaozhong; Wang, Zhongfa; Bu, Yikun; Chen, Lujian; Cai, Guoxiong; Huang, Wencai; Cai, Zhiping; Chen, Nan
2016-02-01
For a linearly variable Fabry-Perot filter, the peak transmission wavelengths change linearly with the transverse position shift of the substrate. Such a Fabry-Perot filter is designed and fabricated and used as an output coupler of a c-cut Nd:YVO4 laser experimentally in this paper to obtain a 1062 and 1083 nm dual-wavelength laser. The peak transmission wavelengths are gradually shifted from 1040.8 to 1070.8 nm. The peak transmission wavelength of the Fabry-Perot filter used as the output coupler for the dual-wavelength laser is 1068 nm and resides between 1062 and 1083 nm, which makes the transmissions of the desired dual wavelengths change in opposite slopes with the transverse shift of the filter. Consequently, powers of the two wavelengths change in opposite directions. A branch power, oppositely tunable 1062 and 1083 nm dual-wavelength laser is successfully demonstrated. Design principles of the linear variable Fabry-Perot filter used as an output coupler are discussed. Advantages of the method are summarized.
Institute of Scientific and Technical Information of China (English)
Xuehua Ye; Yaoju Zhang; Junfeng Chen
2007-01-01
In solid immersion lens (SIL) microscopy systems with high numerical aperture (NA), there always exists the aberration produced by Fresnel effects at the interface between SIL and the sample. This aberration may cause the degradation of the image of sample. We design a continuous phase filter and optimize the optical field distribution of SIL system. The numerical results show that when the continuous phase filter is used, the field distribution of SIL system can be optimized, and the focal depth and intensity of transmitted light can be increased. At the same time, the intensity of side-lobe and the resolution are kept almost unchanged.
An Optimal Orthogonal Decomposition Method for Kalman Filter-Based Turbofan Engine Thrust Estimation
Litt, Jonathan S.
2007-01-01
A new linear point design technique is presented for the determination of tuning parameters that enable the optimal estimation of unmeasured engine outputs, such as thrust. The engine's performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters related to each major engine component. Accurate thrust reconstruction depends on knowledge of these health parameters, but there are usually too few sensors to be able to estimate their values. In this new technique, a set of tuning parameters is determined that accounts for degradation by representing the overall effect of the larger set of health parameters as closely as possible in a least squares sense. The technique takes advantage of the properties of the singular value decomposition of a matrix to generate a tuning parameter vector of low enough dimension that it can be estimated by a Kalman filter. A concise design procedure to generate a tuning vector that specifically takes into account the variables of interest is presented. An example demonstrates the tuning parameters ability to facilitate matching of both measured and unmeasured engine outputs, as well as state variables. Additional properties of the formulation are shown to lend themselves well to diagnostics.
Optimizing Cost of Continuous Overlapping Queries over Data Streams by Filter Adaption
Xie, Qing
2016-01-12
The problem we aim to address is the optimization of cost management for executing multiple continuous queries on data streams, where each query is defined by several filters, each of which monitors certain status of the data stream. Specially the filter can be shared by different queries and expensive to evaluate. The conventional objective for such a problem is to minimize the overall execution cost to solve all queries, by planning the order of filter evaluation in shared strategy. However, in streaming scenario, the characteristics of data items may change in process, which can bring some uncertainty to the outcome of individual filter evaluation, and affect the plan of query execution as well as the overall execution cost. In our work, considering the influence of the uncertain variation of data characteristics, we propose a framework to deal with the dynamic adjustment of filter ordering for query execution on data stream, and focus on the issues of cost management. By incrementally monitoring and analyzing the results of filter evaluation, our proposed approach can be effectively adaptive to the varied stream behavior and adjust the optimal ordering of filter evaluation, so as to optimize the execution cost. In order to achieve satisfactory performance and efficiency, we also discuss the trade-off between the adaptivity of our framework and the overhead incurred by filter adaption. The experimental results on synthetic and two real data sets (traffic and multimedia) show that our framework can effectively reduce and balance the overall query execution cost and keep high adaptivity in streaming scenario.
Directory of Open Access Journals (Sweden)
M. Manimozhi
2014-05-01
Full Text Available Fault Detection and Isolation (FDI using Linear Kalman Filter (LKF is not sufficient for effective monitoring of nonlinear processes. Most of the chemical plants are nonlinear in nature while operating the plant in a wide range of process variables. In this study we present an approach for designing of Multi Model Adaptive Linear Kalman Filter (MMALKF for Fault Detection and Isolation (FDI of a nonlinear system. The uses a bank of adaptive Kalman filter, with each model based on different fault hypothesis. In this study the effectiveness of the MMALKF has been demonstrated on a spherical tank system. The proposed method is detecting and isolating the sensor and actuator soft faults which occur sequentially or simultaneously.
SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA
Directory of Open Access Journals (Sweden)
Karsten Rodenacker
2011-05-01
Full Text Available Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D is gathered during relatively long time ranges (3-5 min. From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters. Filters applied are compared by classifications of activations.
Optimal Prefix Free Code: word-RAM Linear and Algebraic Instance Optimal
Barbay, Jérémy
2012-01-01
We describe a new technique to compute an optimal prefix-free code over $\\alphabetSize$ symbols from their frequencies $\\{\\frequency_1,..,\\frequency_\\alphabetSize\\}$. This technique yields an algorithm running in linear time in the $\\Omega(\\lg \\alphabetSize)$-word RAM model when each frequency holds into $\\Oh(1)$ words, hence improving on the $\\Oh(\\alphabetSize\\lg\\lg\\alphabetSize)$ solution based on sorting in the word RAM model. In a more restricted model, this yields also an algorithm performing $\\Oh(\\alphabetSize(1{+}\\entropy(\\alphabetSize_1,...,\\alphabetSize_\
Adaptive Conflict-Free Optimization of Rule Sets for Network Security Packet Filtering Devices
Directory of Open Access Journals (Sweden)
Andrea Baiocchi
2015-01-01
Full Text Available Packet filtering and processing rules management in firewalls and security gateways has become commonplace in increasingly complex networks. On one side there is a need to maintain the logic of high level policies, which requires administrators to implement and update a large amount of filtering rules while keeping them conflict-free, that is, avoiding security inconsistencies. On the other side, traffic adaptive optimization of large rule lists is useful for general purpose computers used as filtering devices, without specific designed hardware, to face growing link speeds and to harden filtering devices against DoS and DDoS attacks. Our work joins the two issues in an innovative way and defines a traffic adaptive algorithm to find conflict-free optimized rule sets, by relying on information gathered with traffic logs. The proposed approach suits current technology architectures and exploits available features, like traffic log databases, to minimize the impact of ACO development on the packet filtering devices. We demonstrate the benefit entailed by the proposed algorithm through measurements on a test bed made up of real-life, commercial packet filtering devices.
Linear variable filter based oil condition monitoring systems for offshore windturbines
Wiesent, Benjamin R.; Dorigo, Daniel G.; Şimşek, Özlem; Koch, Alexander W.
2011-10-01
A major part of future renewable energy will be generated in offshore wind farms. The used turbines of the 5 MW class and beyond, often feature a planetary gear with 1000 liters lubricating oil or even more. Monitoring the oil aging process provides early indication of necessary maintenance and oil change. Thus maintenance is no longer time-scheduled but becomes wear dependent providing ecological and economical benefits. This paper describes two approaches based on a linear variable filter (LVF) as dispersive element in a setup of a cost effective infrared miniature spectrometer for oil condition monitoring purposes. Spectra and design criteria of a static multi-element detector and a scanning single element detector system are compared and rated. Both LVF miniature spectrometers are appropriately designed for the suggested measurements but have certain restrictions. LVF multi-channel sensors combined with sophisticated multivariate data processing offer the possibility to use the sensor for a broad range of lubricants just by a software update of the calibration set. An all-purpose oil sensor may be obtained.
Directory of Open Access Journals (Sweden)
Muhammad Ammirrul Atiqi Mohd Zainuri
2016-05-01
Full Text Available This paper presents improvement of a harmonics extraction algorithm, known as the fundamental active current (FAC adaptive linear element (ADALINE neural network with the integration of photovoltaic (PV to shunt active power filters (SAPFs as active current source. Active PV injection in SAPFs should reduce dependency on grid supply current to supply the system. In addition, with a better and faster harmonics extraction algorithm, the SAPF should perform well, especially under dynamic PV and load conditions. The role of the actual injection current from SAPF after connecting PVs will be evaluated, and the better effect of using FAC ADALINE will be confirmed. The proposed SAPF was simulated and evaluated in MATLAB/Simulink first. Then, an experimental laboratory prototype was also developed to be tested with a PV simulator (CHROMA 62100H-600S, and the algorithm was implemented using a TMS320F28335 Digital Signal Processor (DSP. From simulation and experimental results, significant improvements in terms of total harmonic distortion (THD, time response and reduction of source power from grid have successfully been verified and achieved.
Energy Technology Data Exchange (ETDEWEB)
Viana, Rodrigo S.S.; Tardelli, Tiago C.; Yoriyaz, Helio, E-mail: hyoriyaz@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil); Jackowski, Marcel P., E-mail: mjack@ime.usp.b [University of Sao Paulo (USP), SP (Brazil). Dept. of Computer Science
2011-07-01
In recent years, a new technique for in vivo spectrographic imaging of stable isotopes was presented as Neutron Stimulated Emission Computed Tomography (NSECT). In this technique, a fast neutrons beam stimulates stable nuclei in a sample, which emit characteristic gamma radiation. The photon energy is unique and is used to identify the emitting nuclei. The emitted gamma energy spectra can be used for reconstruction of the target tissue image and for determination of the tissue elemental composition. Due to the stochastic nature of photon emission process by irradiated tissue, one of the most suitable algorithms for tomographic reconstruction is the Expectation-Maximization (E-M) algorithm, once on its formulation are considered simultaneously the probabilities of photons emission and detection. However, a disadvantage of this algorithm is the introduction of noise in the reconstructed image as the number of iterations increases. This increase can be caused either by features of the algorithm itself or by the low sampling rate of projections used for tomographic reconstruction. In this work, a linear filter in the frequency domain was used in order to improve the quality of the reconstructed images. (author)
Tabus, I; Petrescu, D; Gabbouj, M
1996-01-01
A training framework is developed in this paper to design optimal nonlinear filters for various signal and image processing tasks. The targeted families of nonlinear filters are the Boolean filters and stack filters. The main merit of this framework at the implementation level is perhaps the absence of constraining models, making it nearly universal in terms of application areas. We develop fast procedures to design optimal or close to optimal filters, based on some representative training set. Furthermore, the training framework shows explicitly the essential part of the initial specification and how it affects the resulting optimal solution. Symmetry constraints are imposed on the data and, consequently, on the resulting optimal solutions for improved performance and ease of implementation. The case study is dedicated to natural images. The properties of optimal Boolean and stack filters, when the desired signal in the training set is the image of a natural scene, are analyzed. Specifically, the effect of changing the desired signal (using various natural images) and the characteristics of the noise (the probability distribution function, the mean, and the variance) is analyzed. Elaborate experimental conditions were selected to investigate the robustness of the optimal solutions using a sensitivity measure computed on data sets. A remarkably low sensitivity and, consequently, a good generalization power of Boolean and stack filters are revealed. Boolean-based filters are thus shown to be not only suitable for image restoration but also robust, making it possible to build libraries of "optimal" filters, which are suitable for a set of applications.
Swarm Intelligence for Optimizing Hybridized Smoothing Filter in Image Edge Enhancement
Rao, B. Tirumala; Dehuri, S.; Dileep, M.; Vindhya, A.
In this modern era, image transmission and processing plays a major role. It would be impossible to retrieve information from satellite and medical images without the help of image processing techniques. Edge enhancement is an image processing step that enhances the edge contrast of an image or video in an attempt to improve its acutance. Edges are the representations of the discontinuities of image intensity functions. For processing these discontinuities in an image, a good edge enhancement technique is essential. The proposed work uses a new idea for edge enhancement using hybridized smoothening filters and we introduce a promising technique of obtaining best hybrid filter using swarm algorithms (Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO)) to search for an optimal sequence of filters from among a set of rather simple, representative image processing filters. This paper deals with the analysis of the swarm intelligence techniques through the combination of hybrid filters generated by these algorithms for image edge enhancement.
Frequency invariant beamforming via optimal array pattern synthesis and FIR filters design
Institute of Scientific and Technical Information of China (English)
YAN Shefeng; MA Yuanliang
2005-01-01
An approach to designing time domain broadband frequency invariant beamformer via optimal array pattern synthesis and optimal FIR filters design is proposed. First, the working frequency band is decomposed into a number of narrow band frequency bins. The array weights at each frequency bin are designed via optimal array pattern synthesis methods to insure that the synthesized pattern approximates the desired one within the mainlobe area.Then, a bank of FIR filters corresponding to the input channels are designed to provide the frequency responses that approximate the array weights in the working frequency band for each sensor. Finally, each sensor feeds a FIR filter and the filter outputs are summed to produce the beam output time series. Both array pattern synthesis and FIR filters design problems are formulated as the second-order cone programming (SOCP), which can be easily solved using well-developed interior-point methods. Results of computer simulations and lake-experiment for a twelve-element semicircular array demonstrate satisfactory performance of the proposed approach.
Lim, Wei Jer; Neoh, Siew Chin; Norizan, Mohd Natashah; Mohamad, Ili Salwani
2015-05-01
Optimization for complex circuit design often requires large amount of manpower and computational resources. In order to optimize circuit performance, it is critical not only for circuit designers to adjust the component value but also to fulfill objectives such as gain, cutoff frequency, ripple and etc. This paper proposes Non-dominated Sorting Genetic Algorithm II (NSGA-II) to optimize a ninth order multiple feedback Chebyshev low pass filter. Multi-objective Pareto-Based optimization is involved whereby the research aims to obtain the best trade-off for minimizing the pass-band ripple, maximizing the output gain and achieving the targeted cut-off frequency. The developed NSGA-II algorithm is executed on the NGSPICE circuit simulator to assess the filter performance. Overall results show satisfactory in the achievements of the required design specifications.
Ding, Ze-Min; Chen, Lin-Gen; Ge, Yan-Lin; Sun, Feng-Rui
2016-04-01
A theoretical model for energy selective electron (ESE) heat pumps operating with two-dimensional electron reservoirs is established in this study. In this model, a double-resonance energy filter operating with a total momentum filtering mechanism is considered for the transmission of electrons. The optimal thermodynamic performance of the ESE heat pump devices is also investigated. Numerical calculations show that the heating load of the device with two resonances is larger, whereas the coefficient of performance (COP) is lower than the ESE heat pump when considering a single-resonance filter. The performance characteristics of the ESE heat pumps in the total momentum filtering condition are generally superior to those with a conventional filtering mechanism. In particular, the performance characteristics of the ESE heat pumps considering a conventional filtering mechanism are vastly different from those of a device with total momentum filtering, which is induced by extra electron momentum in addition to the horizontal direction. Parameters such as resonance width and energy spacing are found to be associated with the performance of the electron system.
Raffensperger, Jeff P.; Baker, Anna C.; Blomquist, Joel D.; Hopple, Jessica A.
2017-06-26
Quantitative estimates of base flow are necessary to address questions concerning the vulnerability and response of the Nation’s water supply to natural and human-induced change in environmental conditions. An objective of the U.S. Geological Survey National Water-Quality Assessment Project is to determine how hydrologic systems are affected by watershed characteristics, including land use, land cover, water use, climate, and natural characteristics (geology, soil type, and topography). An important component of any hydrologic system is base flow, generally described as the part of streamflow that is sustained between precipitation events, fed to stream channels by delayed (usually subsurface) pathways, and more specifically as the volumetric discharge of water, estimated at a measurement site or gage at the watershed scale, which represents groundwater that discharges directly or indirectly to stream reaches and is then routed to the measurement point.Hydrograph separation using a recursive digital filter was applied to 225 sites in the Chesapeake Bay watershed. The recursive digital filter was chosen for the following reasons: it is based in part on the assumption that groundwater acts as a linear reservoir, and so has a physical basis; it has only two adjustable parameters (alpha, obtained directly from recession analysis, and beta, the maximum value of the base-flow index that can be modeled by the filter), which can be determined objectively and with the same physical basis of groundwater reservoir linearity, or that can be optimized by applying a chemical-mass-balance constraint. Base-flow estimates from the recursive digital filter were compared with those from five other hydrograph-separation methods with respect to two metrics: the long-term average fraction of streamflow that is base flow, or base-flow index, and the fraction of days where streamflow is entirely base flow. There was generally good correlation between the methods, with some biased
Directory of Open Access Journals (Sweden)
B. Shank
2014-11-01
Full Text Available We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs connected to quasiparticle (qp traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
Shank, B; Cabrera, B; Kreikebaum, J M; Moffatt, R; Redl, P; Young, B A; Brink, P L; Cherry, M; Tomada, A
2014-01-01
We present a detailed thermal and electrical model of superconducting transition edge sensors (TESs) connected to quasiparticle (qp) traps, such as the W TESs connected to Al qp traps used for CDMS (Cryogenic Dark Matter Search) Ge and Si detectors. We show that this improved model, together with a straightforward time-domain optimal filter, can be used to analyze pulses well into the nonlinear saturation region and reconstruct absorbed energies with optimal energy resolution.
A Temperature-to-Digital Converter Based on an Optimized Electrothermal Filter
Kashmiri, S.M.; Xia, S.; Makinwa, K.A.A.
2009-01-01
This paper describes the design of a CMOS temperature-to-digital converter (TDC). It operates by measuring the temperature-dependent phase shift of an electrothermal filter (ETF). Compared to previous work, this TDC employs an ETF whose layout has been optimized to minimize the thermal phase spread
Khaki, Mehdi; Forootan, Ehsan; Kuhn, Michael; Awange, Joseph; Pattiaratchi, Charitha
2016-04-01
Quantifying large-scale (basin/global) water storage changes is essential to understand the Earth's hydrological water cycle. Hydrological models have usually been used to simulate variations in storage compartments resulting from changes in water fluxes (i.e., precipitation, evapotranspiration and runoff) considering physical or conceptual frameworks. Models however represent limited skills in accurately simulating the storage compartments that could be the result of e.g., the uncertainty of forcing parameters, model structure, etc. In this regards, data assimilation provides a great chance to combine observational data with a prior forecast state to improve both the accuracy of model parameters and to improve the estimation of model states at the same time. Various methods exist that can be used to perform data assimilation into hydrological models. The one more frequently used particle-based algorithms suitable for non-linear systems high-dimensional systems is the Ensemble Kalman Filtering (EnKF). Despite efficiency and simplicity (especially in EnKF), this method indicate some drawbacks. To implement EnKF, one should use the sample covariance of observations and model state variables to update a priori estimates of the state variables. The sample covariance can be suboptimal as a result of small ensemble size, model errors, model nonlinearity, and other factors. Small ensemble can also lead to the development of correlations between state components that are at a significant distance from one another where there is no physical relation. To investigate the under-sampling issue raise by EnKF, covariance inflation technique in conjunction with localization was implemented. In this study, a comparison between latest methods used in the data assimilation framework, to overcome the mentioned problem, is performed. For this, in addition to implementing EnKF, we introduce and apply the Local Ensemble Kalman Filter (LEnKF) utilizing covariance localization to remove
Havens, Timothy C.; Cummings, Ian; Botts, Jonathan; Summers, Jason E.
2017-05-01
The linear ordered statistic (LOS) is a parameterized ordered statistic (OS) that is a weighted average of a rank-ordered sample. LOS operators are useful generalizations of aggregation as they can represent any linear aggregation, from minimum to maximum, including conventional aggregations, such as mean and median. In the fuzzy logic field, these aggregations are called ordered weighted averages (OWAs). Here, we present a method for learning LOS operators from training data, viz., data for which you know the output of the desired LOS. We then extend the learning process with regularization, such that a lower complexity or sparse LOS can be learned. Hence, we discuss what 'lower complexity' means in this context and how to represent that in the optimization procedure. Finally, we apply our learning methods to the well-known constant-false-alarm-rate (CFAR) detection problem, specifically for the case of background levels modeled by long-tailed distributions, such as the K-distribution. These backgrounds arise in several pertinent imaging problems, including the modeling of clutter in synthetic aperture radar and sonar (SAR and SAS) and in wireless communications.
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
This paper proposed a design method for delay-dependent robust H-infinity filter of linear systems with uncertainty and time-varying interval delay.The proposed method was shown to be much simpler than existing ones while giving significant improvement to the existing results.The key step in the method was to construct a special type of Lyapunov functional for the filter design problem.Unlike the existing techniques,the proposed method employed neither free weighting matrices nor any model transformation,le...
Jie, Cui; Lei, Chen; Peng, Zhao; Xu, Niu; Yi, Liu
2014-06-01
A broadband monolithic linear single pole, eight throw (SP8T) switch has been fabricated in 180 nm thin film silicon-on-insulator (SOI) CMOS technology with a quad-band GSM harmonic filter in integrated passive devices (IPD) technology, which is developed for cellular applications. The antenna switch module (ASM) features 1.2 dB insertion loss with filter on 2G bands and 0.4 dB insertion loss in 3G bands, less than -45 dB isolation and maximum -103 dB intermodulation distortion for mobile front ends by applying distributed architecture and adaptive supply voltage generator.
Simultaneous optimization of decisions using a linear utility function
Vos, Hendrik J.
1988-01-01
The purpose of this paper is to simultaneously optimize decision rules for combinations of elementary decisions. As a result of this approach, rules are found that make more efficient use of the data than does optimizing those decisions separately. The framework for the approach is derived from empi
Optimal angle reduction - a behavioral approach to linear system approximation
Roorda, Berend; Fuhrmann, P.A.
2001-01-01
We investigate the problem of optimal state reduction under minimization of the angle between system behaviors. The angle is defined in a worst-case sense, as the largest angle that can occur between a system trajectory and its optimal approximation in the reduced-order model. This problem is analyz
Optimization for decision making linear and quadratic models
Murty, Katta G
2010-01-01
While maintaining the rigorous linear programming instruction required, Murty's new book is unique in its focus on developing modeling skills to support valid decision-making for complex real world problems, and includes solutions to brand new algorithms.
Comparison of Kalman filter and optimal smoother estimates of spacecraft attitude
Sedlak, J.
1994-01-01
Given a valid system model and adequate observability, a Kalman filter will converge toward the true system state with error statistics given by the estimated error covariance matrix. The errors generally do not continue to decrease. Rather, a balance is reached between the gain of information from new measurements and the loss of information during propagation. The errors can be further reduced, however, by a second pass through the data with an optimal smoother. This algorithm obtains the optimally weighted average of forward and backward propagating Kalman filters. It roughly halves the error covariance by including future as well as past measurements in each estimate. This paper investigates whether such benefits actually accrue in the application of an optimal smoother to spacecraft attitude determination. Tests are performed both with actual spacecraft data from the Extreme Ultraviolet Explorer (EUVE) and with simulated data for which the true state vector and noise statistics are exactly known.
Optimization of Filter by using Support Vector Regression Machine with Cuckoo Search Algorithm
Directory of Open Access Journals (Sweden)
M. İlarslan
2014-09-01
Full Text Available Herein, a new methodology using a 3D Electromagnetic (EM simulator-based Support Vector Regression Machine (SVRM models of base elements is presented for band-pass filter (BPF design. SVRM models of elements, which are as fast as analytical equations and as accurate as a 3D EM simulator, are employed in a simple and efficient Cuckoo Search Algorithm (CSA to optimize an ultra-wideband (UWB microstrip BPF. CSA performance is verified by comparing it with other Meta-Heuristics such as Genetic Algorithm (GA and Particle Swarm Optimization (PSO. As an example of the proposed design methodology, an UWB BPF that operates between the frequencies of 3.1 GHz and 10.6 GHz is designed, fabricated and measured. The simulation and measurement results indicate in conclusion the superior performance of this optimization methodology in terms of improved filter response characteristics like return loss, insertion loss, harmonic suppression and group delay.
Optimization of spectrally selective Si/SiO2 based filters for thermophotovoltaic devices
Khosroshahi, Farhad Kazemi; Ertürk, Hakan; Pınar Mengüç, M.
2017-08-01
Design of a spectrally selective filter based on one-dimensional Si/SiO2 layers is considered for improved performance of thermo-photovoltaic devices. Spectrally selective filters transmit only the convertible radiation from the emitter as non-convertible radiation leads to a reduction in cell efficiency due to heating. The presented Si/SiO2 based filter concept reflects the major part of the undesired range back to the emitter to minimize energy required for the process and it is adaptable to different types of cells and emitters with different temperatures since its cut-off wavelength can be tuned. While this study mainly focuses on InGaSb based thermo-photovoltaic cell, Si, GaSb, and Ga0.78In0.22As0.19Sb0.81 based cells are also examined. Transmittance of the structure is predicted by rigorous coupled wave approach. Genetic algorithm, which is a global optimization method, is used to find the best possible filter structure by considering the overall efficiency as an objective function that is maximized. The simulations show that significant enhancement in the overall system and device efficiency is possible by using such filters with TPV devices. The methodology described in this paper allows for an improved filter design procedure for selected applications.
Lattice Structure for Paraunitary Linear-phase Filter Banks with Accuracy
Institute of Scientific and Technical Information of China (English)
Hong Ying XIAO
2006-01-01
Multivariate filter banks with a polyphase matrix built by matrix factorization (lattice structure) were proposed to obtain orthonormal wavelet basis. On the basis of that, we propose a general method of constructing filter banks which ensure second and third accuracy of its corresponding scaling function. In the last part, examples with second and third accuracy are given.
Glentis, George-Othon; Slump, Cornelis H.; Hermann, Otto E.
2000-01-01
In this paper a novel algorithm is presented for the efficient two-dimensional (2-D), mean squared error (MSE), FIR filtering and system identification. Filter masks of general boundaries are allowed. Efficient order updating recursions are developed by exploiting the spatial shift invariance
Directory of Open Access Journals (Sweden)
Shaoxing Hu
2015-11-01
Full Text Available Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted “useful” data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency.
Hu, Shaoxing; Xu, Shike; Wang, Duhu; Zhang, Aiwu
2015-11-11
Aiming at addressing the problem of high computational cost of the traditional Kalman filter in SINS/GPS, a practical optimization algorithm with offline-derivation and parallel processing methods based on the numerical characteristics of the system is presented in this paper. The algorithm exploits the sparseness and/or symmetry of matrices to simplify the computational procedure. Thus plenty of invalid operations can be avoided by offline derivation using a block matrix technique. For enhanced efficiency, a new parallel computational mechanism is established by subdividing and restructuring calculation processes after analyzing the extracted "useful" data. As a result, the algorithm saves about 90% of the CPU processing time and 66% of the memory usage needed in a classical Kalman filter. Meanwhile, the method as a numerical approach needs no precise-loss transformation/approximation of system modules and the accuracy suffers little in comparison with the filter before computational optimization. Furthermore, since no complicated matrix theories are needed, the algorithm can be easily transplanted into other modified filters as a secondary optimization method to achieve further efficiency.
Design Optimization of Vena Cava Filters: An application to dual filtration devices
Energy Technology Data Exchange (ETDEWEB)
Singer, M A; Wang, S L; Diachin, D P
2009-12-03
Pulmonary embolism (PE) is a significant medical problem that results in over 300,000 fatalities per year. A common preventative treatment for PE is the insertion of a metallic filter into the inferior vena cava that traps thrombi before they reach the lungs. The goal of this work is to use methods of mathematical modeling and design optimization to determine the configuration of trapped thrombi that minimizes the hemodynamic disruption. The resulting configuration has implications for constructing an optimally designed vena cava filter. Computational fluid dynamics is coupled with a nonlinear optimization algorithm to determine the optimal configuration of trapped model thrombus in the inferior vena cava. The location and shape of the thrombus are parameterized, and an objective function, based on wall shear stresses, determines the worthiness of a given configuration. The methods are fully automated and demonstrate the capabilities of a design optimization framework that is broadly applicable. Changes to thrombus location and shape alter the velocity contours and wall shear stress profiles significantly. For vena cava filters that trap two thrombi simultaneously, the undesirable flow dynamics past one thrombus can be mitigated by leveraging the flow past the other thrombus. Streamlining the shape of thrombus trapped along the cava wall reduces the disruption to the flow, but increases the area exposed to abnormal wall shear stress. Computer-based design optimization is a useful tool for developing vena cava filters. Characterizing and parameterizing the design requirements and constraints is essential for constructing devices that address clinical complications. In addition, formulating a well-defined objective function that quantifies clinical risks and benefits is needed for designing devices that are clinically viable.
Fuzzy optimization of primal-dual pair using piecewise linear membership functions
Directory of Open Access Journals (Sweden)
Pandey D.
2012-01-01
Full Text Available Present paper improves the model of Bector and Chandra [Fuzzy Sets and Systems, 125 (2002 317-325] on duality in fuzzy linear programming by using non-linear membership functions. Numerical problem discussed by these authors has also been worked out through our non-linear model to demonstrate improved optimality of the results.
Optimal Design of High-Order Passive-Damped Filters for Grid-Connected Applications
DEFF Research Database (Denmark)
Beres, Remus Narcis; Wang, Xiongfei; Blaabjerg, Frede
2016-01-01
design procedures, the proposed method simplifies the iterative design of the overall filter while ensuring the minimum resonance peak with a lower damping capacitor and a lower rated resistor. It is shown that there is only one optimal value of the damping resistor or quality factor to achieve a minimum......Harmonic stability problems caused by the resonance of high-order filters in power electronic systems are ever increasing. The use of passive damping does provide a robust solution to address these issues, but at the price of reduced efficiency due to the presence of additional passive components...
A Filter-Based Uniform Algorithm for Optimizing Top-k Query in Distributed Networks
Institute of Scientific and Technical Information of China (English)
ZHAO Zhibin; YAO Lan; YANG Xiaochun; LI Binyang; YU Ge
2006-01-01
In this paper we propose a Filter-based Uniform Algorithm (FbUA) for optimizing top-k query in distributed networks, which has been a topic of much recent interest.The basic idea of FbUA is to set a filter at each node to prevent it from sending out the data with little chance to contribute to the top-k result.FbUA can gain exact answers to top-k query through two phrases of round-trip communications between query station and participant nodes.The experiment results show that FbUA reduces network bandwidth consumption dramatically.
Statistically-Efficient Filtering in Impulsive Environments: Weighted Myriad Filters
Directory of Open Access Journals (Sweden)
Gonzalez Juan G
2002-01-01
Full Text Available Linear filtering theory has been largely motivated by the characteristics of Gaussian signals. In the same manner, the proposed Myriad Filtering methods are motivated by the need for a flexible filter class with high statistical efficiency in non-Gaussian impulsive environments that can appear in practice. Myriad filters have a solid theoretical basis, are inherently more powerful than median filters, and are very general, subsuming traditional linear FIR filters. The foundation of the proposed filtering algorithms lies in the definition of the myriad as a tunable estimator of location derived from the theory of robust statistics. We prove several fundamental properties of this estimator and show its optimality in practical impulsive models such as the -stable and generalized- . We then extend the myriad estimation framework to allow the use of weights. In the same way as linear FIR filters become a powerful generalization of the mean filter, filters based on running myriads reach all of their potential when a weighting scheme is utilized. We derive the "normal" equations for the optimal myriad filter, and introduce a suboptimal methodology for filter tuning and design. The strong potential of myriad filtering and estimation in impulsive environments is illustrated with several examples.
Institute of Scientific and Technical Information of China (English)
崔鹏; 张承慧
2007-01-01
The finite time horizon indefinite linear quadratic(LQ) optimal control problem for singular linear discrete time-varying systems is discussed. Indefinite LQ optimal control problem for singular systems can be transformed to that for standard state-space systems under a reasonable assumption. It is shown that the indefinite LQ optimal control problem is dual to that of projection for backward stochastic systems. Thus, the optimal LQ controller can be obtained by computing the gain matrices of Kalman filter.Necessary and sufficient conditions guaranteeing a unique solution for the indefinite LQ problem are given. An explicit solution for the problem is obtained in terms of the solution of Riccati difference equations.
A New Mutated Quantum-Behaved Particle Swarm Optimizer for Digital IIR Filter Design
Directory of Open Access Journals (Sweden)
Wenbo Xu
2009-01-01
Full Text Available Adaptive infinite impulse response (IIR filters have shown their worth in a wide range of practical applications. Because the error surface of IIR filters is multimodal in most cases, global optimization techniques are required for avoiding local minima. In this paper, we employ a global optimization algorithm, Quantum-behaved particle swarm optimization (QPSO that was proposed by us previously, and its mutated version in the design of digital IIR filter. The mechanism in QPSO is based on the quantum behaviour of particles in a potential well and particle swarm optimization (PSO algorithm. QPSO is characterized by fast convergence, good search ability, and easy implementation. The mutated QPSO (MuQPSO is proposed in this paper by using a random vector in QPSO to increase the randomness and to enhance the global search ability. Experimental results on three examples show that QPSO and MuQPSO are superior to genetic algorithm (GA, differential evolution (DE algorithm, and PSO algorithm in quality, convergence speed, and robustness.
Tractable Latent State Filtering for Non-Linear DSGE Models Using a Second-Order Approximation
Kollmann, Robert
2013-01-01
This paper develops a novel approach for estimating latent state variables of Dynamic Stochastic General Equilibrium (DSGE) models that are solved using a second-order accurate approximation. I apply the Kalman filter to a state-space representation of the second-order solution based on the ‘pruning’ scheme of Kim, Kim, Schaumburg and Sims (2008). By contrast to particle filters, no stochastic simulations are needed for the filter here--the present method is thus much faster. In Monte Carlo e...
Qin, Sitian; Fan, Dejun; Su, Peng; Liu, Qinghe
2014-04-01
In this paper, the optimization techniques for solving pseudoconvex optimization problems are investigated. A simplified recurrent neural network is proposed according to the optimization problem. We prove that the optimal solution of the optimization problem is just the equilibrium point of the neural network, and vice versa if the equilibrium point satisfies the linear constraints. The proposed neural network is proven to be globally stable in the sense of Lyapunov and convergent to an exact optimal solution of the optimization problem. A numerical simulation is given to illustrate the global convergence of the neural network. Applications in business and chemistry are given to demonstrate the effectiveness of the neural network.
Directory of Open Access Journals (Sweden)
Xintao Xia
2013-05-01
Full Text Available In this study, we propose the improved relative-entropy of the ideal circle function to the measured information of the radius error of the workpiece surface to make an eccentricity filtering in roundness measurement. Along with a correct assessment for the parameters of the eccentricity filtering, the extracted information from the measured information is obtained by the minimization of the improved relative-entropy. The case studies show that the information optimization is characterized by decreasing the improved relative-entropy, the extracted information almost coincides with the real information, the improved relative-entropy has a strong immunity to the stochastic disturbance of the rough work piece-surface and the increase of the minimum of the improved relative-entropy counteracts the effect of the stochastic disturbance on the assessment for parameters in eccentricity filtering.
Directory of Open Access Journals (Sweden)
Suksan Tiyarachakun
2014-01-01
Full Text Available This paper presents a novel harmonic identification algorithm of shunt active power filter for balanced and unbalanced three-phase systems based on the instantaneous power theory called instantaneous power theory with Fourier. Moreover, the optimal design of predictive current controller using an artificial intelligence technique called adaptive Tabu search is also proposed in the paper. These enhancements of the identification and current control parts are the aim of the good performance for shunt active power filter. The good results for harmonic mitigation using the proposed ideas in the paper are confirmed by the intensive simulation using SPS in SIMULINK. The simulation results show that the enhanced shunt active power filter can provide the minimum %THD (Total Harmonic Distortion of source currents and unity power factor after compensation. In addition, the %THD also follows the IEEE Std.519-1992.
Head movement as an artefact of optimal solutions to linearization ...
African Journals Online (AJOL)
IT
or a child acquiring the language to infer the original syntactic information from the signal and ... explore it, will turn out to require head movement as an inalienable property. The effect of head movement will follow from a general linearization algorithm which, in turn, is motivated by ...... In colloquial usage the negative.
Subramanian, Aneesh C.
2012-11-01
This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slaved modes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinear model where fast and slow variables modulate each other. This suggests that the analysis step in the PFs maintains the balance in both variables much better than the EnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.
Vorobjev, Ivan A; Buchholz, Kathrin; Prabhat, Prashant; Ketman, Kenneth; Egan, Elizabeth S; Marti, Matthias; Duraisingh, Manoj T; Barteneva, Natasha S
2012-09-05
Malaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP)-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP) labelling is complicated by autofluorescence (AF) of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP. Detection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry. A new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP) and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP), AF was markedly decreased and signal-background improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites. Filter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis of parasite-infected samples with in the intention of gene
Directory of Open Access Journals (Sweden)
Vorobjev Ivan A
2012-09-01
Full Text Available Abstract Background Malaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP labelling is complicated by autofluorescence (AF of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP. Methods Detection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry. Results A new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP, AF was markedly decreased and signal-background improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites. Discussion Filter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis
Linear Span of the Optimal Frequency Hopping Sequences from Irreducible Cyclic Co des
Institute of Scientific and Technical Information of China (English)
GAO Juntao; HU Yupu; LI Xuelian
2015-01-01
Optimal set of the frequency hopping se-quences can be derived from some irreducible cyclic codes. This paper determines the linear span of the frequency hopping sequences in the optimal set. The linear span is much less than the length of the frequency hopping se-quences. In order to improve the linear span, we use two types of permutation polynomials, power permutation and binomial permutation, to transform the optimal set of the frequency hopping sequences. The transformed frequency hopping sequences have optimal Hamming correlation and larger linear span than the original frequency hopping se-quences. Compared with the original frequency hopping sequences, the transformed optimal frequency hopping se-quences have higher security to resist the cryptanalytic method.
PAPR reduction in FBMC using an ACE-based linear programming optimization
van der Neut, Nuan; Maharaj, Bodhaswar TJ; de Lange, Frederick; González, Gustavo J.; Gregorio, Fernando; Cousseau, Juan
2014-12-01
This paper presents four novel techniques for peak-to-average power ratio (PAPR) reduction in filter bank multicarrier (FBMC) modulation systems. The approach extends on current PAPR reduction active constellation extension (ACE) methods, as used in orthogonal frequency division multiplexing (OFDM), to an FBMC implementation as the main contribution. The four techniques introduced can be split up into two: linear programming optimization ACE-based techniques and smart gradient-project (SGP) ACE techniques. The linear programming (LP)-based techniques compensate for the symbol overlaps by utilizing a frame-based approach and provide a theoretical upper bound on achievable performance for the overlapping ACE techniques. The overlapping ACE techniques on the other hand can handle symbol by symbol processing. Furthermore, as a result of FBMC properties, the proposed techniques do not require side information transmission. The PAPR performance of the techniques is shown to match, or in some cases improve, on current PAPR techniques for FBMC. Initial analysis of the computational complexity of the SGP techniques indicates that the complexity issues with PAPR reduction in FBMC implementations can be addressed. The out-of-band interference introduced by the techniques is investigated. As a result, it is shown that the interference can be compensated for, whilst still maintaining decent PAPR performance. Additional results are also provided by means of a study of the PAPR reduction of the proposed techniques at a fixed clipping probability. The bit error rate (BER) degradation is investigated to ensure that the trade-off in terms of BER degradation is not too severe. As illustrated by exhaustive simulations, the SGP ACE-based technique proposed are ideal candidates for practical implementation in systems employing the low-complexity polyphase implementation of FBMC modulators. The methods are shown to offer significant PAPR reduction and increase the feasibility of FBMC as
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
This paper proposes a distributed denial-of-service attack detection method based on self similar and wavelet analysis. This method adopts an optimized transmission control protocol cookie technology for filter optimization in order to accurately detect and efficiently filter the traffic of distributed denial-of-service attack. This paper presents the design of our software, and describes all important algorithms of detection and filtering. Experimental results showed that our method has only a low delay to detect abnormal traffic of distributed denial-of-service attacks, and with a high percentage of filtering.
Quality classification of wooden surfaces using Gabor filters and genetic feature optimization
Poelzleitner, Wolfgang; Schwingskakl, Gert
1999-08-01
We apply a model of texture segmentation using multiple spatially and spectrally localized filters, known as Gabor filters, to the analysis of texture and effect regions found on wooden boards. Specifically we present a method to find an optimal set of parameters for a given 2D object detection method. The method uses banks of Gabor filters to limit the rang of spatial frequencies, where mutually distinct textures differ significantly in their dominant characterizing frequencies. By encoding images into multiple narrow spatial frequency and orientation channels a local classification of texture regions can be achieved. Unlike other methods applying Gabor filters, we do not use a full Gabor transform, but use feature selection techniques to maximize discrimination. The selection method uses a genetic algorithm to optimize various parameters of the system including Gabor weights, and the parameters of morphological pre-processing. We demonstrate the applicability of the method to the task of classifying wooden textures, and report experimental results using the proposed method.
Filter QP-free Method with Piecewise Linear NCP Function%分片线性NCP函数滤子QP-free算法
Institute of Scientific and Technical Information of China (English)
濮定国; 孔祥庆; 王新长
2009-01-01
本文定义了分片线性NCP函数,并对非线性约束优化问题,提出了带有这分片NCP函数的QP-free非可行域算法.利用优化问题的一阶KKT条件,乘子和NCP函数,得到对应的非光滑方程组.本文给出解这非光滑方程组算法,它包含原始-对偶变量,在局部意义下,可看成关扰动牛顿-拟牛顿迭代算法.在线性搜索时,这算法采用滤子方法.本文给出的算法是可实现的并具有全局收敛性,在适当假设下算法具有超线性收敛性.%In this paper, we define a piecewise linear NCP function and propose a filter QP-free infeasible method with this NCP function for constrained nonlinear optimization problems. This iterative method is based on the solution of nonsmooth equations which are obtained by the multipliers and the NCP function for the KKT first-order opti-mality conditions. Locally, each iteration of this method can be viewed as a perturbation of a Newton-quasi Newton iteration on both the primal and dual variables for the solution of the KKT optimality conditions. We also use the filter on linear searches. This method is implementable and globally convergent. We also prove that the method has superlinear convergence rate under some mild conditions.
He, Yunlong; Zhao, Yanna; Ren, Yanju; Gee, James
2017-01-01
Filtering belongs to the most fundamental operations of retinal image processing and for which the value of the filtered image at a given location is a function of the values in a local window centered at this location. However, preserving thin retinal vessels during the filtering process is challenging due to vessels' small area and weak contrast compared to background, caused by the limited resolution of imaging and less blood flow in the vessel. In this paper, we present a novel retinal image denoising approach which is able to preserve the details of retinal vessels while effectively eliminating image noise. Specifically, our approach is carried out by determining an optimal spatial kernel for the bilateral filter, which is represented by a line spread function with an orientation and scale adjusted adaptively to the local vessel structure. Moreover, this approach can also be served as a preprocessing tool for improving the accuracy of the vessel detection technique. Experimental results show the superiority of our approach over state-of-the-art image denoising techniques such as the bilateral filter. PMID:28261320
Directory of Open Access Journals (Sweden)
Waad Bouaguel
2012-08-01
Full Text Available Filter selection techniques are known for their simplicity and efficiency. However this kind of methods doesn’t take into consideration the features inter-redundancy. Consequently the un-removed redundant features remain in the final classification model, giving lower generalization performance. In this paper we propose to use a mathematical optimization method that reduces inter-features redundancy and maximize relevance between each feature and the target variable.
Flat-top Drop Filter based on a Single Topology Optimized Photonic Crystal Cavity
DEFF Research Database (Denmark)
Frandsen, Lars Hagedorn; Elesin, Yuriy; Guan, Xiaowei
2015-01-01
Outperforming conventional design concepts, a flat-top drop filter has been designed byapplying 3D topology optimization to a single waveguide-coupled L3 photonic crystal cavity.Measurements on the design fabricated in silicon-on-insulator material reveal that the pass-band ofthe drop channel...... is flat within 0.44 dB over a wavelength range of 9.7 nm with an insertion losslower than 0.85 dB....
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The optimal control problem was studied for linear time-varying systems, which was affected by external persistent disturbances with known dynamic characteristics but unknown initial conditions. To damp the effect of disturbances in an optimal fashion, we obtained a new feedforward and feedback optimal control law and gave the control algorithm by solving a Riccati differential equation and a matrix differential equation. Simulation results showed that the achieved optimal control law was realizable, efficient and robust to reject the external disturbances.
DEFF Research Database (Denmark)
Sørensen, Rene; Lund, Erik
2013-01-01
This extended abstract presents a new parameterization for performing discrete material and thickness optimization of laminated composite structures. The parameterization is based on the work by Sørensen and Lund 2013, where we present a reformulation of the original parameterization....... The reformulation eliminates the need for having explicit constraint for ensuring that intermediate void does not appear in between layers of the laminate. This is achieved by utilizing a filtering technique known as a casting constraint from traditional topology optimization with isotropic materials....
Optimal spectral filtering in soliton self-frequency shift for deep-tissue multiphoton microscopy
Wang, Ke; Qiu, Ping
2015-05-01
Tunable optical solitons generated by soliton self-frequency shift (SSFS) have become valuable tools for multiphoton microscopy (MPM). Recent progress in MPM using 1700 nm excitation enabled visualizing subcortical structures in mouse brain in vivo for the first time. Such an excitation source can be readily obtained by SSFS in a large effective-mode-area photonic crystal rod with a 1550-nm fiber femtosecond laser. A longpass filter was typically used to isolate the soliton from the residual in order to avoid excessive energy deposit on the sample, which ultimately leads to optical damage. However, since the soliton was not cleanly separated from the residual, the criterion for choosing the optimal filtering wavelength is lacking. Here, we propose maximizing the ratio between the multiphoton signal and the n'th power of the excitation pulse energy as a criterion for optimal spectral filtering in SSFS when the soliton shows dramatic overlapping with the residual. This optimization is based on the most efficient signal generation and entirely depends on physical quantities that can be easily measured experimentally. Its application to MPM may reduce tissue damage, while maintaining high signal levels for efficient deep penetration.
Deso, Steven E; Idakoji, Ibrahim A; Muelly, Michael C; Kuo, William T
2016-06-01
Owing to a myriad of inferior vena cava (IVC) filter types and their potential complications, rapid and correct identification may be challenging when encountered on routine imaging. The authors aimed to develop an interactive mobile application that allows recognition of all IVC filters and related complications, to optimize the care of patients with indwelling IVC filters. The FDA Premarket Notification Database was queried from 1980 to 2014 to identify all IVC filter types in the United States. An electronic search was then performed on MEDLINE and the FDA MAUDE database to identify all reported complications associated with each device. High-resolution photos were taken of each filter type and corresponding computed tomographic and fluoroscopic images were obtained from an institutional review board-approved IVC filter registry. A wireframe and storyboard were created, and software was developed using HTML5/CSS compliant code. The software was deployed using PhoneGap (Adobe, San Jose, CA), and the prototype was tested and refined. Twenty-three IVC filter types were identified for inclusion. Safety data from FDA MAUDE and 72 relevant peer-reviewed studies were acquired, and complication rates for each filter type were highlighted in the application. Digital photos, fluoroscopic images, and CT DICOM files were seamlessly incorporated. All data were succinctly organized electronically, and the software was successfully deployed into Android (Google, Mountain View, CA) and iOS (Apple, Cupertino, CA) platforms. A powerful electronic mobile application was successfully created to allow rapid identification of all IVC filter types and related complications. This application may be used to optimize the care of patients with IVC filters.
Optimization of interference filters with genetic algorithms applied to silver-based heat mirrors.
Eisenhammer, T; Lazarov, M; Leutbecher, M; Schöffel, U; Sizmann, R
1993-11-01
In the optimization of multilayer stacks for various optical filtering purposes not only the thicknesses of the thin films are to be optimized, but also the sequence of materials. Materials with very different optical properties, such as metals and dielectrics, may be combined. A genetic algorithm is introduced to search for the optimal sequence of materials along with their optical thicknesses. This procedure is applied to a heat mirror in combination with a blackbody absorber for thermal solar energy applications at elevated temperatures (250 °C). The heat mirror is based on silver films with antireflective dielectric layers. Seven dielectrics have been considered. For a five-layer stack the sequence (TiO(2)/Ag/TiO(2)/Ag/Y(2)O(3)) is found to be optimal.
Optimization of contrast-enhanced breast imaging: Analysis using a cascaded linear system model.
Hu, Yue-Houng; Scaduto, David A; Zhao, Wei
2017-01-01
Contrast-enhanced (CE) breast imaging involves the injection contrast agents (i.e., iodine) to increase conspicuity of malignant lesions. CE imaging may be used in conjunction with digital mammography (DM) or digital breast tomosynthesis (DBT) and has shown promise in improving diagnostic specificity. Both CE-DM and CE-DBT techniques require optimization as clinical diagnostic tools. Physical factors including x-ray spectra, subtraction technique, and the signal from iodine contrast, must be considered to provide the greatest object detectability and image quality. We developed a cascaded linear system model (CLSM) for the optimization of CE-DM and CE-DBT employing dual energy (DE) subtraction or temporal (TE) subtraction. We have previously developed a CLSM for DBT implemented with an a-Se flat panel imager (FPI) and filtered backprojection (FBP) reconstruction algorithm. The model is used to track image quality metrics - modulation transfer function (MTF) and noise power spectrum (NPS) - at each stage of the imaging chain. In this study, the CLSM is extended for CE breast imaging. The effect of x-ray spectrum (varied by changing tube potential and the filter) and DE and TE subtraction techniques on breast structural noise was measured was studied and included as a deterministic source of noise in the CLSM. From the two-dimensional (2D) and three-dimensional (3D) MTF and NPS, the ideal observer signal-to-noise ratio (SNR), also known as the detectability index (d'), may be calculated. Using d' as a FOM, we discuss the optimization of CE imaging for the task of iodinated contrast object detection within structured backgrounds. Increasing x-ray energy was determined to decrease the magnitude of structural noise and not its correlation. By performing DE subtraction, the magnitude of the structural noise was further reduced at the expense of increased stochastic (quantum and electronic) noise. TE subtraction exhibited essentially no residual structural noise at the
Royston, T. J.; Singh, R.
1996-07-01
While significant non-linear behavior has been observed in many vibration mounting applications, most design studies are typically based on the concept of linear system theory in terms of force or motion transmissibility. In this paper, an improved analytical strategy is presented for the design optimization of complex, active of passive, non-linear mounting systems. This strategy is built upon the computational Galerkin method of weighted residuals, and incorporates order reduction and numerical continuation in an iterative optimization scheme. The overall dynamic characteristics of the mounting system are considered and vibratory power transmission is minimized via adjustment of mount parameters by using both passive and active means. The method is first applied through a computational example case to the optimization of basic passive and active, non-linear isolation configurations. It is found that either active control or intentionally introduced non-linearity can improve the mount's performance; but a combination of both produces the greatest benefit. Next, a novel experimental, active, non-linear isolation system is studied. The effect of non-linearity on vibratory power transmission and active control are assessed via experimental measurements and the enhanced Galerkin method. Results show how harmonic excitation can result in multiharmonic vibratory power transmission. The proposed optimization strategy offers designers some flexibility in utilizing both passive and active means in combination with linear and non-linear components for improved vibration mounts.
Particle filter initialization in non-linear non-Gaussian radar target tracking
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
When particle filter is applied in radar target tracking,the accuracy of the initial particles greatly effects the results of filtering. For acquiring more accurate initial particles,a new method called"competition strategy algorithm"is presented.In this method,initial measurements give birth to several particle groups around them,regularly.Each of the groups is tested several times,separately,in the beginning periods,and the group that has the most number of efficient particles is selected as the initial particles.For this method,sample initial particles selected are on the basis of several measurements instead of only one first measurement,which surely improves the accuracy of initial particles.The method sacrifices initialization time and computation cost for accuracy of initial particles. Results of simulation show that it greely improves the accuracy of initial particles,which makes the effect of filtering much better.
Optimal linear shrinkage corrections of sample LMMSE and MVDR estimators
2012-01-01
La proposició d'estimadors shrinkage òptims que corregeixen la degradació dels mètodes sample LMMSE i sample MUDR en el règim on el número de mostres és petit en comparació a la dimensió de les observacions. [ANGLÈS] This master thesis proposes optimal shrinkage estimators that counteract the performance degradation of the sample LMMSE and sample MVDR methods in the regime where the sample size is small compared to the observation dimension. [CASTELLÀ] Esta máster tesis propone estimado...
A Way to Find All the Optimal Solutions in Linear Programming
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
With the expression theorem of convex polyhedron, this paper gives the general expres sion for the solutions in standard linear programming problems. And the calculation procedures in determining the optimal solutions are also given.
Global Optimization for Sum of Linear Ratios Problem Using New Pruning Technique
Directory of Open Access Journals (Sweden)
2009-02-01
Full Text Available A global optimization algorithm is proposed for solving sum of general linear ratios problem (P using new pruning technique. Firstly, an equivalent problem (P1 of the (P is derived by exploiting the characteristics of linear constraints. Then, by utilizing linearization method the relaxation linear programming (RLP of the (P1 can be constructed and the proposed algorithm is convergent to the global minimum of the (P through the successive refinement of the linear relaxation of feasible region and solutions of a series of (RLP. Then, a new pruning technique is proposed, this technique offers a possibility to cut away a large part of the current investigated feasible region by the optimization algorithm, which can be utilized as an accelerating device for global optimization of problem (P. Finally, the numerical experiments are given to illustrate the feasibility of the proposed algorithm.
Directory of Open Access Journals (Sweden)
J. Briem
2017-09-01
Full Text Available This paper presents an electrical, fully integrated, high quality (Q factor GmC bandpass filter (BPF stage for a wireless 27 MHz direct conversion receiver for a bendable sensor system-in-foil (Briem et al., 2016. The core of the BPF with a Q factor of more than 200 is an operational transconductance amplifier (OTA with a high linearity at an input range of up to 300 mVpp, diff. The OTA's signal-to-noise-and-distortion-ratio (SNDR of more than 80 dB in the mentioned range is achieved by stabilizing its transconductance Gm with a respective feedback loop and a source degeneration resistors RDG. The filter stage can be tuned and is tolerant to global and local process variations due to offset and common-mode feedback (CMFB control circuits. The results are determined by periodic steady state (PSS simulations at more than 200 global and local process variation parameter and temperature points and corner simulations. It is expected, that the parasitic elements of the layout have no significant influence on the filter behaviour. The current consumption of the whole filter stage is less than 600 µA.
Briem, Jochen; Mader, Marco; Reiter, Daniel; Amirpour, Raul; Grözing, Markus; Berroth, Manfred
2017-09-01
This paper presents an electrical, fully integrated, high quality (Q) factor GmC bandpass filter (BPF) stage for a wireless 27 MHz direct conversion receiver for a bendable sensor system-in-foil (Briem et al., 2016). The core of the BPF with a Q factor of more than 200 is an operational transconductance amplifier (OTA) with a high linearity at an input range of up to 300 mVpp, diff. The OTA's signal-to-noise-and-distortion-ratio (SNDR) of more than 80 dB in the mentioned range is achieved by stabilizing its transconductance Gm with a respective feedback loop and a source degeneration resistors RDG. The filter stage can be tuned and is tolerant to global and local process variations due to offset and common-mode feedback (CMFB) control circuits. The results are determined by periodic steady state (PSS) simulations at more than 200 global and local process variation parameter and temperature points and corner simulations. It is expected, that the parasitic elements of the layout have no significant influence on the filter behaviour. The current consumption of the whole filter stage is less than 600 µA.
Sajedi, Salar; Kamal Asl, Alireza; Ay, Mohammad R; Farahani, Mohammad H; Rahmim, Arman
2013-06-01
Applications in imaging and spectroscopy rely on pulse processing methods for appropriate data generation. Often, the particular method utilized does not highly impact data quality, whereas in some scenarios, such as in the presence of high count rates or high frequency pulses, this issue merits extra consideration. In the present study, a new approach for pulse processing in nuclear medicine imaging and spectroscopy is introduced and evaluated. The new non-linear recursive filter (NLRF) performs nonlinear processing of the input signal and extracts the main pulse characteristics, having the powerful ability to recover pulses that would ordinarily result in pulse pile-up. The filter design defines sampling frequencies lower than the Nyquist frequency. In the literature, for systems involving NaI(Tl) detectors and photomultiplier tubes (PMTs), with a signal bandwidth considered as 15 MHz, the sampling frequency should be at least 30 MHz (the Nyquist rate), whereas in the present work, a sampling rate of 3.3 MHz was shown to yield very promising results. This was obtained by exploiting the known shape feature instead of utilizing a general sampling algorithm. The simulation and experimental results show that the proposed filter enhances count rates in spectroscopy. With this filter, the system behaves almost identically as a general pulse detection system with a dead time considerably reduced to the new sampling time (300 ns). Furthermore, because of its unique feature for determining exact event times, the method could prove very useful in time-of-flight PET imaging.
Optimal MPC for tracking of constrained linear systems
Ferramosca, A.; Limon, D.; Alvarado, I.; Alamo, T.; Castaño, F.; Camacho, E. F.
2011-08-01
Model predictive control (MPC) is one of the few techniques which is able to handle constraints on both state and input of the plant. The admissible evolution and asymptotic convergence of the closed-loop system is ensured by means of suitable choice of the terminal cost and terminal constraint. However, most of the existing results on MPC are designed for a regulation problem. If the desired steady-state changes, the MPC controller must be redesigned to guarantee the feasibility of the optimisation problem, the admissible evolution as well as the asymptotic stability. Recently, a novel MPC has been proposed to ensure the feasibility of the optimisation problem, constraints satisfaction and asymptotic evolution of the system to any admissible target steady-state. A drawback of this controller is the loss of a desirable property of the MPC controllers: the local optimality property. In this article, a novel formulation of the MPC for tracking is proposed aimed to recover the optimality property maintaining all the properties of the original formulation.
Pacheco, Sara E; Anderson, Linnea M; Boekelheide, Kim
2012-01-01
Quantifying testicular homogenization-resistant spermatid heads (HRSH) is a powerful indicator of spermatogenesis. These counts have traditionally been performed manually using a hemocytometer, but this method can be time consuming and biased. We aimed to develop a protocol to reduce debris for the application of automated counting, which would allow for efficient and unbiased quantification of rat HRSH. We developed a filter-lysis protocol that effectively removes debris from rat testicular homogenates. After filtering and lysing the homogenates, we found no statistical differences between manual (classic and filter-lysis) and automated (filter-lysis) counts using 1-way analysis of variance with Bonferroni's multiple comparison test. In addition, Pearson's correlation coefficients were calculated to compare the counting methods, and there was a strong correlation between the classic manual counts and the filter-lysis manual (r = 0.85, P = .002) and the filter-lysis automated (r = 0.89, P = .0005) counts. We also tested the utility of the automated method in a low-dose exposure model known to decrease HRSH. Adult Fischer 344 rats exposed to 0.33% 2,5-hexanedione in the drinking water for 12 weeks demonstrated decreased body (P = .02) and testes (P = .002) weights. In addition, there was a significant reduction in the number of HRSH per testis (P = .002) when compared to controls. A filterlysis protocol was optimized to purify rat testicular homogenates for automated HRSH counts. Automated counting systems yield unbiased data and can be applied to detect changes in the testis after low-dose toxicant exposure.
Optimal Pole Assignment of Linear Systems by the Sylvester Matrix Equations
Directory of Open Access Journals (Sweden)
Hua-Feng He
2014-01-01
class of linear matrix equations, necessary and sufficient conditions for the existence of a solution to the optimal pole assignment problem are proposed in this paper. By properly choosing the free parameters in the parametric solutions to this class of linear matrix equations, complete solutions to the optimal pole assignment problem can be obtained. A numerical example is used to illustrate the effectiveness of the proposed approach.
A new approach on designing l1 optimal regulator with minimum order for SISO linear systems
Institute of Scientific and Technical Information of China (English)
Xiang LIU
2006-01-01
For a SISO linear discrete-time system with a specified input signal, a novel method to realize optimal l1 regulation control is presented. Utilizing the technique of converting a polynomial equation to its corresponding matrix equation, a linear programming problem to get an optimal l1 norm of the system output error map is developed which includes the first term and the last term of the map sequence in the objective function and the right vector of its constraint matrix equation, respectively. The adjustability for the width of the constraint matrix makes the trade-off between the order of the optimal regulator and the value of the minimum objective norm become possible, especially for achieving the optimal regulator with minimum order. By norm scaling rules for the constraint matrix equation, the optimal solution can be scaled directly or be obtained by solving a linear programming problem with l1 norm objective.
Theoretical analysis of highly linear tunable filters using Switched-Resistor techniques
Jiraseree-amornkun, Amorn; Jiraseree-Amornkun, A.; Worapishet, Apisak; Klumperink, Eric A.M.; Nauta, Bram; Surakampontorn, Wanlop
2008-01-01
Abstract—In this paper, an in-depth analysis of switched-resistor (S-R) techniques for implementing low-voltage low-distortion tunable active-RC filters is presented. The S-R techniques make use of switch(es) with duty-cycle-controlled clock(s) to achieve tunability of the effective resistance and,
Institute of Scientific and Technical Information of China (English)
王铁成; 李伟力; 孙建伟
2003-01-01
A mathematical model has been built up for compound cage rotor induction machine with the rotor re-sistance and leakage inductance in the model identified through Kalman filtering method. Using the identifiedparameters, simulation studies are performed, and simulation results are compared with testing results.
Robust C subroutines for non-linear optimization
DEFF Research Database (Denmark)
Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun
2004-01-01
to worry about special parameters controlling the iterations. For convenience we include an option for numerical checking of the user s implementation of the gradient. Note that another report [3] presents a collection of robust subroutines for both unconstrained and constrained optimization...... by changing 1 to 0. The present report is a new and updated version of a previous report NI-91-03 with the same title, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated from Fortran to C. The reason for writing the present report is that some...... of the C subroutines have been replaced by more effective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modi ed to some extent. For a description of the original Fortran subroutines see the report [17]. The software...
2014-11-01
for Time Accurate Compressible Large Eddy Simulations : Comparison of Artificial Dissipation and Filtering Schemes 5b. GRANT NUMBER 5c. PROGRAM...Optimal Numerical Schemes for Time Accurate Compressible Large Eddy Simulations : Comparison of Artificial Dissipation and Filtering Schemes 67th
Approximating the Pareto Set of Multiobjective Linear Programs via Robust Optimization
Gorissen, B.L.; den Hertog, D.
2012-01-01
Abstract: The Pareto set of a multiobjective optimization problem consists of the solutions for which one or more objectives can not be improved without deteriorating one or more other objectives. We consider problems with linear objectives and linear constraints and use Adjustable Robust Optimizati
Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood
Asadi, A.R.; Roos, C.
2015-01-01
In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortu
Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood
Asadi, A.R.; Roos, C.
2015-01-01
In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author.
Infeasible Interior-Point Methods for Linear Optimization Based on Large Neighborhood
Asadi, A.R.; Roos, C.
2015-01-01
In this paper, we design a class of infeasible interior-point methods for linear optimization based on large neighborhood. The algorithm is inspired by a full-Newton step infeasible algorithm with a linear convergence rate in problem dimension that was recently proposed by the second author. Unfortu
Directory of Open Access Journals (Sweden)
Mohamed G. Egila
2016-12-01
Full Text Available This paper presents a proposed design for analyzing electrocardiography (ECG signals. This methodology employs highpass least-square linear phase Finite Impulse Response (FIR filtering technique to filter out the baseline wander noise embedded in the input ECG signal to the system. Discrete Wavelet Transform (DWT was utilized as a feature extraction methodology to extract the reduced feature set from the input ECG signal. The design uses back propagation neural network classifier to classify the input ECG signal. The system is implemented on Xilinx 3AN-XC3S700AN Field Programming Gate Array (FPGA board. A system simulation has been done. The design is compared with some other designs achieving total accuracy of 97.8%, and achieving reduction in utilizing resources on FPGA implementation.
Wang, Li-Qi; Ge, Hui-Fang; Li, Gui-Bin; Yu, Dian-Yu; Hu, Li-Zhi; Jiang, Lian-Zhou
2014-04-01
Combining classical Kalman filter with NIR analysis technology, a new method of characteristic wavelength variable selection, namely Kalman filtering method, is presented. The principle of Kalman filter for selecting optimal wavelength variable was analyzed. The wavelength selection algorithm was designed and applied to NIR detection of soybean oil acid value. First, the PLS (partial leastsquares) models were established by using different absorption bands of oil. The 4 472-5 000 cm(-1) characteristic band of oil acid value, including 132 wavelengths, was selected preliminarily. Then the Kalman filter was used to select characteristic wavelengths further. The PLS calibration model was established using selected 22 characteristic wavelength variables, the determination coefficient R2 of prediction set and RMSEP (root mean squared error of prediction) are 0.970 8 and 0.125 4 respectively, equivalent to that of 132 wavelengths, however, the number of wavelength variables was reduced to 16.67%. This algorithm is deterministic iteration, without complex parameters setting and randomicity of variable selection, and its physical significance was well defined. The modeling using a few selected characteristic wavelength variables which affected modeling effect heavily, instead of total spectrum, can make the complexity of model decreased, meanwhile the robustness of model improved. The research offered important reference for developing special oil near infrared spectroscopy analysis instruments on next step.
Houts, R. C.; Vaughn, G. L.
1974-01-01
Three algorithms are developed for designing finite impulse response digital filters to be used for pulse shaping and channel equalization. The first is the Minimax algorithm which uses linear programming to design a frequency-sampling filter with a pulse shape that approximates the specification in a minimax sense. Design examples are included which accurately approximate a specified impulse response with a maximum error of 0.03 using only six resonators. The second algorithm is an extension of the Minimax algorithm to design preset equalizers for channels with known impulse responses. Both transversal and frequency-sampling equalizer structures are designed to produce a minimax approximation of a specified channel output waveform. Examples of these designs are compared as to the accuracy of the approximation, the resultant intersymbol interference (ISI), and the required transmitted energy. While the transversal designs are slightly more accurate, the frequency-sampling designs using six resonators have smaller ISI and energy values.
Optimized Waterspace Management and Scheduling Using Mixed-Integer Linear Programming
2016-01-01
TECHNICAL REPORT NSWC PCD TR 2015-003 OPTIMIZED WATERSPACE MANAGEMENT AND SCHEDULING USING MIXED-INTEGER LINEAR PROGRAMMING...constraints required for the mathematical formulation of the MCM scheduling problem pertaining to the survey constraints and logistics management . The...Floudas, Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications, Oxford University Press, 1995. [10] M. J. Bays, A. Shende, D. J
An Image Filter Based on Shearlet Transformation and Particle Swarm Optimization Algorithm
Directory of Open Access Journals (Sweden)
Kai Hu
2015-01-01
Full Text Available Digital image is always polluted by noise and made data postprocessing difficult. To remove noise and preserve detail of image as much as possible, this paper proposed image filter algorithm which combined the merits of Shearlet transformation and particle swarm optimization (PSO algorithm. Firstly, we use classical Shearlet transform to decompose noised image into many subwavelets under multiscale and multiorientation. Secondly, we gave weighted factor to those subwavelets obtained. Then, using classical Shearlet inverse transform, we obtained a composite image which is composed of those weighted subwavelets. After that, we designed fast and rough evaluation method to evaluate noise level of the new image; by using this method as fitness, we adopted PSO to find the optimal weighted factor we added; after lots of iterations, by the optimal factors and Shearlet inverse transform, we got the best denoised image. Experimental results have shown that proposed algorithm eliminates noise effectively and yields good peak signal noise ratio (PSNR.
DEFF Research Database (Denmark)
Sørensen, Rene; Lund, Erik
2013-01-01
This extended abstract presents a new parameterization for performing discrete material and thickness optimization of laminated composite structures. The parameterization is based on the work by Sørensen and Lund 2013, where we present a reformulation of the original parameterization. The reformu......This extended abstract presents a new parameterization for performing discrete material and thickness optimization of laminated composite structures. The parameterization is based on the work by Sørensen and Lund 2013, where we present a reformulation of the original parameterization....... The reformulation eliminates the need for having explicit constraint for ensuring that intermediate void does not appear in between layers of the laminate. This is achieved by utilizing a filtering technique known as a casting constraint from traditional topology optimization with isotropic materials....
Zhang, Shengzhi; Yu, Shuai; Liu, Chaojun; Yuan, Xuebing; Liu, Sheng
2016-02-20
To provide a long-time reliable orientation, sensor fusion technologies are widely used to integrate available inertial sensors for the low-cost orientation estimation. In this paper, a novel dual-linear Kalman filter was designed for a multi-sensor system integrating MEMS gyros, an accelerometer, and a magnetometer. The proposed filter precludes the impacts of magnetic disturbances on the pitch and roll which the heading is subjected to. The filter can achieve robust orientation estimation for different statistical models of the sensors. The root mean square errors (RMSE) of the estimated attitude angles are reduced by 30.6% under magnetic disturbances. Owing to the reduction of system complexity achieved by smaller matrix operations, the mean total time consumption is reduced by 23.8%. Meanwhile, the separated filter offers greater flexibility for the system configuration, as it is possible to switch on or off the second stage filter to include or exclude the magnetometer compensation for the heading. Online experiments were performed on the homemade miniature orientation determination system (MODS) with the turntable. The average RMSE of estimated orientation are less than 0.4° and 1° during the static and low-dynamic tests, respectively. More realistic tests on two-wheel self-balancing vehicle driving and indoor pedestrian walking were carried out to evaluate the performance of the designed MODS when high accelerations and angular rates were introduced. Test results demonstrate that the MODS is applicable for the orientation estimation under various dynamic conditions. This paper provides a feasible alternative for low-cost orientation determination.
CSIR Research Space (South Africa)
Cilliers, Jacques E
2009-09-01
Full Text Available In previous paper the authors introduced a technique for generating mismatched pulse compression filters for linear frequency chirp signals. The technique minimizes the sum of the pulse compression sidelobes in an Lp norm sense. It was shown...
Li, Yifan; Liang, Xihui; Zuo, Ming J.
2017-02-01
This paper presents a novel signal processing scheme, diagonal slice spectrum assisted optimal scale morphological filter (DSS-OSMF), for rolling element fault diagnosis. In this scheme, the concept of quadratic frequency coupling (QFC) is firstly defined and the ability of diagonal slice spectrum (DSS) in detection QFC is derived. The DSS-OSMF possesses the merits of depressing noise and detecting QFC. It can remove fault independent frequency components and give a clear representation of fault symptoms. A simulated vibration signal and experimental vibration signals collected from a bearing test rig are employed to evaluate the effectiveness of the proposed method. Results show that the proposed method has a superior performance in extracting fault features of defective rolling element bearing. In addition, comparisons are performed between a multi-scale morphological filter (MMF) and a DSS-OSMF. DSS-OSMF outperforms MMF in detection of an outer race fault and a rolling element fault of a rolling element bearing.
Optimization of dichromatic filters based on photonic heterostructures of Si/MgF2
Guan, Huihuan; Han, Peide; Li, Yuping; Zhou, Hongwei; Zhang, Xue; Zhang, Ruizhen
2012-05-01
The current research work presents the theoretical results of demonstrating novel dichromatic filters, which consist of blue and yellow light. A one-dimensional photonic crystal or photonic heterostructure of Si/MgF2 is analyzed in detail by fully considering the effects of structural parameters using the transfer matrix method. The position and the number of defect modes are shown to have relationships with the repeat cycle counts of various photonic crystals. When the photonic heterostructures have the optimized structural parameters, defect modes can be obtained with high transmittances located in blue and yellow light. This photonic heterostructure is expected to be used in dichromatic filters with wide non-transmission range in a visible range.
DEFF Research Database (Denmark)
Sørensen, Rene; Lund, Erik
2015-01-01
This paper presents a new gradient based method for performing discrete material and thickness optimization of laminated composite structures. The novelty in the new method lies in the application of so-called casting constraints, or thickness filters in this context, to control the thickness...... govern the presence of material in each layer through the thickness of the laminate. Combined with an in-plane density filter, the method enables manufacturers to control the length scale of the geometry while obtaining near discrete designs. Together with the applied manufacturing constraints it is now...... possible for manufacturers to steer the design towards a higher level of manufacturability. The method is demonstrated for mass minimization with displacement and manufacturing constraints. The results show that the method indeed is capable of obtaining near discrete designs which obey the governing...
Optimal Filtering Algorithm-Based Multiuser Detector for Fast Fading CDMA Systems
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
A multiuser detector was developed for fast fading code-division multiple-access systems by representing the channels as a system with the multiplicative noise (SMN) model and then using the known optimal filtering algorithm for the SMN for multiuser detection (MUD). This multiuser detector allows the channel response to be stochastic in one symbol duration, which can be regarded as an effective method of MUD for fast fading CDMA systems. Performance analyses show that the multiuser detector is theoretically valid for CDMA systems over fast fading channels. Simulations show that the multiuser detector performs better than the Kalman filter-based multiuser detector with a faster convergence rate and lower bit error rate.
Feedforward and Feedback Optimal Control for Linear Systems with Sinusoidal Disturbances
Institute of Scientific and Technical Information of China (English)
唐功友
2001-01-01
The linear systems affected by additive external sinusoidal disturbances is studied. he problem is to damp this forced oscillation in an optimal fashion. The main result of this paper is a new design approach is proposed of realizable feedforward and feedback optimal control law for a linear timeinvariant system with sinusoidal disturbances. The algorithm of solving the optimal control law is given. It is shown that the control law is easily realized and is robust with respect to errors produced by the external sinusoidal disturbances through simulation results.
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
A novel method based on ant colony optimization (ACO), algorithm for solving the ill-conditioned linear systems of equations is proposed. ACO is a parallelized bionic optimization algorithm which is inspired from the behavior of real ants. ACO algorithm is first introduced, a kind of positive feedback mechanism is adopted in ACO. Then, the solution problem of linear systems of equations was reformulated as an unconstrained optimization problem for solution by an ACO algorithm. Finally, the ACO with other traditional methods is applied to solve a kind of multi-dimensional Hilbert ill-conditioned linear equations. The numerical results demonstrate that ACO is effective, robust and recommendable in solving ill-conditioned linear systems of equations.
Filter QP-free Method with 3-Piecewise Linear NCP Function%3-分片线性NCP函数的滤子QP-free算法
Institute of Scientific and Technical Information of China (English)
李康弟; 濮定国; 田蔚文
2008-01-01
In this paper, we define a piecewise linear NCP function and propose a filter QP-free infeasible method with this NCP function for constrained nonlinear optimization problems. This iterative method is based on the solution of nonsmooth equations which are obtained by the multipliers and the NCP function for the KKT first-order optimality conditions. Locally, each iteration of this method can be viewed as a perturbation of a mixed Newton-quasi Newton iteration on both the primal and dual variables for the solution of the KKT optimality conditions. We also use the filter on line searches. This method is implementable and globally convergent. We also prove that the method has superlinear convergence rate under some mild conditions.%本文定义一个3-分片线性的NCP函数,并对非线性约束优化问题,提出了带有这分片NCP函数的QP-free非可行域算法.根据优化问题的一阶KKT条件,利用乘子和NCP函数,得到非光滑方程,本文给出一个非光滑方程的迭代算法.这算法包含原始-对偶变量,在局部意义下,可看成关于一阶KKT最优条件的的扰动拟牛顿迭代算法.在线性搜索时,这算法采用滤子方法.本文给出的算法是可实现的并具有全局收敛性,且在适当假设下具有超线性收敛性.
An Adaptive Finite Element Method Based on Optimal Error Estimates for Linear Elliptic Problems
Institute of Scientific and Technical Information of China (English)
汤雁
2004-01-01
The subject of the work is to propose a series of papers about adaptive finite element methods based on optimal error control estimate. This paper is the third part in a series of papers on adaptive finite element methods based on optimal error estimates for linear elliptic problems on the concave corner domains. In the preceding two papers (part 1:Adaptive finite element method based on optimal error estimate for linear elliptic problems on concave corner domain; part 2:Adaptive finite element method based on optimal error estimate for linear elliptic problems on nonconvex polygonal domains), we presented adaptive finite element methods based on the energy norm and the maximum norm. In this paper, an important result is presented and analyzed. The algorithm for error control in the energy norm and maximum norm in part 1 and part 2 in this series of papers is based on this result.
An Optimally Generalized Steepest-Descent Algorithm for Solving Ill-Posed Linear Systems
Directory of Open Access Journals (Sweden)
Chein-Shan Liu
2013-01-01
Full Text Available It is known that the steepest-descent method converges normally at the first few iterations, and then it slows down. We modify the original steplength and descent direction by an optimization argument with the new steplength as being a merit function to be maximized. An optimal iterative algorithm with m-vector descent direction in a Krylov subspace is constructed, of which the m optimal weighting parameters are solved in closed-form to accelerate the convergence speed in solving ill-posed linear problems. The optimally generalized steepest-descent algorithm (OGSDA is proven to be convergent with very fast convergence speed, accurate and robust against noisy disturbance, which is confirmed by numerical tests of some well-known ill-posed linear problems and linear inverse problems.
Kinodynamic RRT*: Optimal Motion Planning for Systems with Linear Differential Constraints
Webb, Dustin J
2012-01-01
We present Kinodynamic RRT*, an incremental sampling-based approach for asymptotically optimal motion planning for robots with linear differential constraints. Our approach extends RRT*, which was introduced for holonomic robots (Karaman et al. 2011), by using a fixed-final-state-free-final-time controller that exactly and optimally connects any pair of states, where the cost function is expressed as a trade-off between the duration of a trajectory and the expended control effort. Our approach generalizes earlier work on extending RRT* to kinodynamic systems, as it guarantees asymptotic optimality for any system with controllable linear dynamics, in state spaces of any dimension. Our approach can be applied to non-linear dynamics as well by using their first-order Taylor approximations. In addition, we show that for the rich subclass of systems with a nilpotent dynamics matrix, closed-form solutions for optimal trajectories can be derived, which keeps the computational overhead of our algorithm compared to tr...
Optimal IIR filter design using Gravitational Search Algorithm with Wavelet Mutation
Directory of Open Access Journals (Sweden)
S.K. Saha
2015-01-01
Full Text Available This paper presents a global heuristic search optimization technique, which is a hybridized version of the Gravitational Search Algorithm (GSA and Wavelet Mutation (WM strategy. Thus, the Gravitational Search Algorithm with Wavelet Mutation (GSAWM was adopted for the design of an 8th-order infinite impulse response (IIR filter. GSA is based on the interaction of masses situated in a small isolated world guided by the approximation of Newtonian’s laws of gravity and motion. Each mass is represented by four parameters, namely, position, active, passive and inertia mass. The position of the heaviest mass gives the near optimal solution. For better exploitation in multidimensional search spaces, the WM strategy is applied to randomly selected particles that enhance the capability of GSA for finding better near optimal solutions. An extensive simulation study of low-pass (LP, high-pass (HP, band-pass (BP and band-stop (BS IIR filters unleashes the potential of GSAWM in achieving better cut-off frequency sharpness, smaller pass band and stop band ripples, smaller transition width and higher stop band attenuation with assured stability.
Optimality analysis of one-step OOSM filtering algorithms in target tracking
Institute of Scientific and Technical Information of China (English)
ZHOU WenHui; LI Lin; CHEN GuoHai; YU AnXi
2007-01-01
In centralized multisensor tracking systems, there are out-of-sequence measurements (OOSMs) frequently arising due to different time delays in communication links and varying pre-processing times at the sensor. Such OOSM arrival can induce the "negative-time measurement update" problem, which is quite common in real multisensor tracking systems. The A1 optimal update algorithm with OOSM is presented by Bar-Shalom for one-step case. However, this paper proves that the optimality of A1 algorithm is lost in direct discrete-time model (DDM) of the process noise, it holds true only in discretized continuous-time model (DCM). One better OOSM filtering algorithm for DDM case is presented. Also, another new optimal OOSM filtering algorithm, which is independent of the discrete time model of the process noise, is presented here. The performance of the two new algorithms is compared with that of A1 algorithm by Monte Carlo simulations. The effectiveness and correctness of the two proposed algorithms are validated by analysis and simulation results.
Strahl, Stefan; Mertins, Alfred
2008-07-18
Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.
Directory of Open Access Journals (Sweden)
Yan Wang
2016-04-01
Full Text Available While many efforts have been devoted to optimizing the power output for a finite-time thermodynamic process, thermodynamic optimization under realistic situations is not necessarily concerned with power alone; rather, it may be of great relevance to optimize generic objective functions that are combinations of power, entropy production, and/or efficiency. One can optimize the objective function for a given model; generally the obtained results are strongly model dependent. However, if the thermodynamic process in question is operated in the linear response regime, then we show in this work that it is possible to adopt a unified approach to optimizing the objective function, thanks to Onsager’s theory of linear irreversible thermodynamics. A dissipation bound is derived, and based on it, the efficiency associated with the optimization problem, which is universal in the linear response regime and irrespective of model details, can be obtained in a unified way. Our results are in good agreement with previous findings. Moreover, we unveil that the ratio between the stopping time of a finite-time process and the optimized duration time plays a pivotal role in determining the corresponding efficiency in the case of linear response.
Directory of Open Access Journals (Sweden)
Khanagha Ali
2010-01-01
Full Text Available Blind identification of MIMO FIR systems has widely received attentions in various fields of wireless data communications. Here, we use Particle Swarm Optimization (PSO as the update mechanism of the well-known inverse filtering approach and we show its good performance compared to original method. Specially, the proposed method is shown to be more robust against lower SNR scenarios or in cases with smaller lengths of available data records. Also, a modified version of PSO is presented which further improves the robustness and preciseness of PSO algorithm. However the most important promise of the modified version is its drastically faster convergence compared to standard implementation of PSO.
Directory of Open Access Journals (Sweden)
Y. Orlov
2002-01-01
Full Text Available The paper is intended to be of tutorial value for Schwartz' distributions theory in nonlinear setting. Mathematical models are presented for nonlinear systems which admit both standard and impulsive inputs. These models are governed by differential equations in distributions whose meaning is generalized to involve nonlinear, non single-valued operating over distributions. The set of generalized solutions of these differential equations is defined via closure, in a certain topology, of the set of the conventional solutions corresponding to standard integrable inputs. The theory is exemplified by mechanical systems with impulsive phenomena, optimal impulsive feedback synthesis, sampled-data filtering of stochastic and deterministic dynamic systems.
DEFF Research Database (Denmark)
Misaridis, Thanasis; Jensen, Jørgen Arendt
1999-01-01
performed with the program Field II. A commercial scanner (B-K Medical 3535) was modified and interfaced to an arbitrary function generator along with an RF power amplifier (Ritec). Hydrophone measurements in water were done to establish excitation voltage and corresponding intensity levels (I-sptp and I......This paper presents a coded excitation imaging system based on a predistorted FM excitation and a digital compression filter designed for medical ultrasonic applications, in order to preserve both axial resolution and contrast. In radars, optimal Chebyshev windows efficiently weight a nearly...