Numerical methods using Matlab

CERN Document Server

Lindfield, George

2012-01-01

Numerical Methods using MATLAB, 3e, is an extensive reference offering hundreds of useful and important numerical algorithms that can be implemented into MATLAB for a graphical interpretation to help researchers analyze a particular outcome. Many worked examples are given together with exercises and solutions to illustrate how numerical methods can be used to study problems that have applications in the biosciences, chaos, optimization, engineering and science across the board. Numerical Methods using MATLAB, 3e, is an extensive reference offering hundreds of use

Matlab differential and integral calculus

CERN Document Server

Lopez, Cesar

2014-01-01

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Differential and Integral Calculus introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. In addition to givi

Matlab programming for numerical analysis

CERN Document Server

Lopez, Cesar

2014-01-01

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. Programming MATLAB for Numerical Analysis introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. You will first become

ORNL ADCP POST-PROCESSING GUIDE AND MATLAB ALGORITHMS FOR MHK SITE FLOW AND TURBULENCE ANALYSIS

Energy Technology Data Exchange (ETDEWEB)

Gunawan, Budi [Oak Ridge National Laboratory (ORNL); Neary, Vincent S [ORNL

2011-09-01

Standard methods, along with guidance for post-processing the ADCP stationary measurements using MATLAB algorithms that were evaluated and tested by Oak Ridge National Laboratory (ORNL), are presented following an overview of the ADCP operating principles, deployment methods, error sources and recommended protocols for removing and replacing spurious data.

Colour based sorting station with Matlab simulation

Directory of Open Access Journals (Sweden)

Constantin Victor

2017-01-01

Full Text Available The paper presents the design process and manufacturing elements of a colour-based sorting station. The system is comprised of a gravitational storage, which also contains the colour sensor. Parts are extracted using a linear pneumatic motor and are fed onto an electrically driven conveyor belt. Extraction of the parts is done at 4 points, using two pneumatic motors and a geared DC motor, while the 4th position is at the end of the belt. The mechanical parts of the system are manufactured using 3D printer technology, allowing for easy modification and adaption to the geometry of different parts. The paper shows all of the stages needed to design, optimize, test and implement the proposed solution. System optimization was performed using a graphical Matlab interface which also allows for sorting algorithm optimization.

MATLAB-implemented estimation procedure for model-based assessment of hepatic insulin degradation from standard intravenous glucose tolerance test data.

Science.gov (United States)

Di Nardo, Francesco; Mengoni, Michele; Morettini, Micaela

2013-05-01

Present study provides a novel MATLAB-based parameter estimation procedure for individual assessment of hepatic insulin degradation (HID) process from standard frequently-sampled intravenous glucose tolerance test (FSIGTT) data. Direct access to the source code, offered by MATLAB, enabled us to design an optimization procedure based on the alternating use of Gauss-Newton's and Levenberg-Marquardt's algorithms, which assures the full convergence of the process and the containment of computational time. Reliability was tested by direct comparison with the application, in eighteen non-diabetic subjects, of well-known kinetic analysis software package SAAM II, and by application on different data. Agreement between MATLAB and SAAM II was warranted by intraclass correlation coefficients ≥0.73; no significant differences between corresponding mean parameter estimates and prediction of HID rate; and consistent residual analysis. Moreover, MATLAB optimization procedure resulted in a significant 51% reduction of CV% for the worst-estimated parameter by SAAM II and in maintaining all model-parameter CV% MATLAB-based procedure was suggested as a suitable tool for the individual assessment of HID process. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

MATLAB for laser speckle contrast analysis (LASCA): a practice-based approach

Science.gov (United States)

Postnikov, Eugene B.; Tsoy, Maria O.; Postnov, Dmitry E.

2018-04-01

Laser Speckle Contrast Analysis (LASCA) is one of the most powerful modern methods for revealing blood dynamics. The experimental design and theory for this method are well established, and the computational recipie is often regarded to be trivial. However, the achieved performance and spatial resolution may considerable differ for different implementations. We comprise a minireview of known approaches to the spatial laser speckle contrast data processing and their realization in MATLAB code providing an explicit correspondence to the mathematical representation, a discussion of available implementations. We also present the algorithm based on the 2D Haar wavelet transform, also supplied with the program code. This new method provides an opportunity to introduce horizontal, vertical and diagonal speckle contrasts; it may be used for processing highly anisotropic images of vascular trees. We provide the comparative analysis of the accuracy of vascular pattern detection and the processing times with a special attention to details of the used MATLAB procedures.

DOOCS environment for FPGA-based cavity control system and control algorithms development

International Nuclear Information System (INIS)

Pucyk, P.; Koprek, W.; Kaleta, P.; Szewinski, J.; Pozniak, K.T.; Czarski, T.; Romaniuk, R.S.

2005-01-01

The paper describes the concept and realization of the DOOCS control software for FPGAbased TESLA cavity controller and simulator (SIMCON). It bases on universal software components, created for laboratory purposes and used in MATLAB based control environment. These modules have been recently adapted to the DOOCS environment to ensure a unified software to hardware communication model. The presented solution can be also used as a general platform for control algorithms development. The proposed interfaces between MATLAB and DOOCS modules allow to check the developed algorithm in the operation environment before implementation in the FPGA. As the examples two systems have been presented. (orig.)

Radioactivity nuclide identification based on BP and LM algorithm neural network

International Nuclear Information System (INIS)

Wang Jihong; Sun Jian; Wang Lianghou

2012-01-01

The paper provides the method which can identify radioactive nuclide based on the BP and LM algorithm neural network. Then, this paper compares the above-mentioned method with FR algorithm. Through the result of the Matlab simulation, the method of radioactivity nuclide identification based on the BP and LM algorithm neural network is superior to the FR algorithm. With the better effect and the higher accuracy, it will be the best choice. (authors)

A Matlab Tool for Tumor Localization in Parathyroid Sestamibi Scintigraphy

Directory of Open Access Journals (Sweden)

M. Đurović

2015-11-01

Full Text Available Submarine method for localization of parathyroid tumors (PT has proved to be effective in case of typical pitfalls of conventional scintigraphic methods (combined subtraction and double phase methods. It uses images obtained by standard dynamic parathyroid sestamibi scintigraphy suggested by European Association of Nuclear Medicine. This paper presents: 1 the developed Matlab interface that enables the implementation and evaluation of algorithms for the automatic application of Submarine method; 2 the algorithm for automatic extraction of the entire thyroid region from the background radioactivity using operations from mathematical morphology applied on dynamic scintigrams; 3 the results obtained by algorithm for localization and visualization of PTs based on estimation of exponential decreasing trend of time-activity curves. The algorithm was tested on a group of 20 patients with histopathologically proven PTs using developed Matlab interface.

Accelerating MATLAB with GPU computing a primer with examples

CERN Document Server

Suh, Jung W

2013-01-01

Beyond simulation and algorithm development, many developers increasingly use MATLAB even for product deployment in computationally heavy fields. This often demands that MATLAB codes run faster by leveraging the distributed parallelism of Graphics Processing Units (GPUs). While MATLAB successfully provides high-level functions as a simulation tool for rapid prototyping, the underlying details and knowledge needed for utilizing GPUs make MATLAB users hesitate to step into it. Accelerating MATLAB with GPUs offers a primer on bridging this gap. Starting with the basics, setting up MATLAB for

Scientific computing an introduction using Maple and Matlab

CERN Document Server

Gander, Walter; Kwok, Felix

2014-01-01

Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple – Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material “hands-on”.

MATLAB-based algorithm to estimate depths of isolated thin dike-like sources using higher-order horizontal derivatives of magnetic anomalies.

Science.gov (United States)

Ekinci, Yunus Levent

2016-01-01

This paper presents an easy-to-use open source computer algorithm (code) for estimating the depths of isolated single thin dike-like source bodies by using numerical second-, third-, and fourth-order horizontal derivatives computed from observed magnetic anomalies. The approach does not require a priori information and uses some filters of successive graticule spacings. The computed higher-order horizontal derivative datasets are used to solve nonlinear equations for depth determination. The solutions are independent from the magnetization and ambient field directions. The practical usability of the developed code, designed in MATLAB R2012b (MathWorks Inc.), was successfully examined using some synthetic simulations with and without noise. The algorithm was then used to estimate the depths of some ore bodies buried in different regions (USA, Sweden, and Canada). Real data tests clearly indicated that the obtained depths are in good agreement with those of previous studies and drilling information. Additionally, a state-of-the-art inversion scheme based on particle swarm optimization produced comparable results to those of the higher-order horizontal derivative analyses in both synthetic and real anomaly cases. Accordingly, the proposed code is verified to be useful in interpreting isolated single thin dike-like magnetized bodies and may be an alternative processing technique. The open source code can be easily modified and adapted to suit the benefits of other researchers.

Slow Orbit Feedback at the ALS Using Matlab

International Nuclear Information System (INIS)

Portmann, G.

1999-01-01

The third generation Advanced Light Source (ALS) produces extremely bright and finely focused photon beams using undulatory, wigglers, and bend magnets. In order to position the photon beams accurately, a slow global orbit feedback system has been developed. The dominant causes of orbit motion at the ALS are temperature variation and insertion device motion. This type of motion can be removed using slow global orbit feedback with a data rate of a few Hertz. The remaining orbit motion in the ALS is only 1-3 micron rms. Slow orbit feedback does not require high computational throughput. At the ALS, the global orbit feedback algorithm, based on the singular valued decomposition method, is coded in MATLAB and runs on a control room workstation. Using the MATLAB environment to develop, test, and run the storage ring control algorithms has proven to be a fast and efficient way to operate the ALS

Co-simulation of Six DOF Wire Driven Parallel Mechanism Based on ADAMS and Matlab

Directory of Open Access Journals (Sweden)

Tang Aofei

2015-01-01

Full Text Available The dynamic model of the 6 DOF Wire Driven Parallel Mechanism (WDPM system is introduced. Based on MATLAB system, the simulation of the inverse dynamic model is achieved. According to the simulation result, the mechanical model for the WDPM system is reasonable. Using ADAMS system, the dynamic model of the virtual prototype is verified by the simulation analysis. The combined control model based on ADAMS/Simulink is derived. The WDPM control system is designed with MATLAB/Simulink. The torque control method is selected for the outer ring and the PD control method for the inner ring. Combined with the ADAMS control model and control law design, the interactive simulation analysis of the WDPM system is completed. According to the simulation results of the spatial circle tracking and line tracking at the end of the moving platform, the tracking error can be reduced by the designed control algorithm. The minimum tracking error is 0.2 mm to 0.3 mm. Therefore, the theoretical foundation for designing hardware systems of the WDPM control system is established.

OMPC: an Open-Source MATLAB-to-Python Compiler.

Science.gov (United States)

Jurica, Peter; van Leeuwen, Cees

2009-01-01

Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

A MATLAB-Aided Method for Teaching Calculus-Based Business Mathematics

Science.gov (United States)

Liang, Jiajuan; Pan, William S. Y.

2009-01-01

MATLAB is a powerful package for numerical computation. MATLAB contains a rich pool of mathematical functions and provides flexible plotting functions for illustrating mathematical solutions. The course of calculus-based business mathematics consists of two major topics: 1) derivative and its applications in business; and 2) integration and its…

Nuclear grade cable thermal life model by time temperature superposition algorithm based on Matlab GUI

International Nuclear Information System (INIS)

Lu Yanyun; Gu Shenjie; Lou Tianyang

2014-01-01

Background: As nuclear grade cable must endure harsh environment within design life, it is critical to predict cable thermal life accurately owing to thermal aging, which is one of dominant factors of aging mechanism. Purpose: Using time temperature superposition (TTS) method, the aim is to construct nuclear grade cable thermal life model, predict cable residual life and develop life model interactive interface under Matlab GUI. Methods: According to TTS, nuclear grade cable thermal life model can be constructed by shifting data groups at various temperatures to preset reference temperature with translation factor which is determined by non linear programming optimization. Interactive interface of cable thermal life model developed under Matlab GUI consists of superposition mode and standard mode which include features such as optimization of translation factor, calculation of activation energy, construction of thermal aging curve and analysis of aging mechanism., Results: With calculation result comparison between superposition and standard method, the result with TTS has better accuracy than that with standard method. Furthermore, confidence level of nuclear grade cable thermal life with TTS is higher than that with standard method. Conclusion: The results show that TTS methodology is applicable to thermal life prediction of nuclear grade cable. Interactive Interface under Matlab GUI achieves anticipated functionalities. (authors)

Introduction to Numerical Computation - analysis and Matlab illustrations

DEFF Research Database (Denmark)

Elden, Lars; Wittmeyer-Koch, Linde; Nielsen, Hans Bruun

In a modern programming environment like eg MATLAB it is possible by simple commands to perform advanced calculations on a personal computer. In order to use such a powerful tool efiiciently it is necessary to have an overview of available numerical methods and algorithms and to know about...... are illustrated by examples in MATLAB....

The NNSYSID Toolbox - A MATLAB Toolbox for System Identification with Neural Networks

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Ravn, Ole; Hansen, Lars Kai

1996-01-01

To assist the identification of nonlinear dynamic systems, a set of tools has been developed for the MATLAB(R) environment. The tools include a number of different model structures, highly effective training algorithms, functions for validating trained networks, and pruning algorithms for determi......To assist the identification of nonlinear dynamic systems, a set of tools has been developed for the MATLAB(R) environment. The tools include a number of different model structures, highly effective training algorithms, functions for validating trained networks, and pruning algorithms...

An introduction to differential equations using MATLAB

CERN Document Server

Butt, Rizwan

2016-01-01

An Introduction to Differential Equations using MATLAB exploits the symbolic, numerical, and graphical capabilitiesof MATLAB to develop a thorough understanding of differential equations algorithms. This book provides the readerwith numerous applications, m-files, and practical examples to problems. Balancing theoretical concepts withcomputational speed and accuracy, the book includes numerous short programs in MATLAB that can be used to solveproblems involving first-and higher-order differential equations, Laplace transforms, linear systems of differentialequations, numerical solutions of differential equations, computer graphics, and more. The author emphasizes thebasic ideas of analytical and numerical techniques and the uses of modern mathematical software (MATLAB) ratherthan relying only on complex mathematical derivations to engineers, mathematician, computer scientists, andphysicists or for use as a textbook in applied or computational courses.A CD-ROM with all the figures, codes, solutions, appendices...

OPTICON: Pro-Matlab software for large order controlled structure design

Science.gov (United States)

Peterson, Lee D.

1989-01-01

A software package for large order controlled structure design is described and demonstrated. The primary program, called OPTICAN, uses both Pro-Matlab M-file routines and selected compiled FORTRAN routines linked into the Pro-Matlab structure. The program accepts structural model information in the form of state-space matrices and performs three basic design functions on the model: (1) open loop analyses; (2) closed loop reduced order controller synthesis; and (3) closed loop stability and performance assessment. The current controller synthesis methods which were implemented in this software are based on the Generalized Linear Quadratic Gaussian theory of Bernstein. In particular, a reduced order Optimal Projection synthesis algorithm based on a homotopy solution method was successfully applied to an experimental truss structure using a 58-state dynamic model. These results are presented and discussed. Current plans to expand the practical size of the design model to several hundred states and the intention to interface Pro-Matlab to a supercomputing environment are discussed.

MATLAB Algorithms for Rapid Detection and Embedding of Palindrome and Emordnilap Electronic Watermarks in Simulated Chemical and Biological Image Data

National Research Council Canada - National Science Library

Robbins, Ronny C

2004-01-01

.... This is similar to words such as STOP which when flipped left right gives the new word POTS. Emordnilap is palindrome spelled backwards. This paper explores the use of MATLAB algorithms in the rapid detection and embedding of palindrome and emordnilap electronic watermarks in simulated chemical and biological Image Data.

Design of high-performance parallelized gene predictors in MATLAB.

Science.gov (United States)

Rivard, Sylvain Robert; Mailloux, Jean-Gabriel; Beguenane, Rachid; Bui, Hung Tien

2012-04-10

This paper proposes a method of implementing parallel gene prediction algorithms in MATLAB. The proposed designs are based on either Goertzel's algorithm or on FFTs and have been implemented using varying amounts of parallelism on a central processing unit (CPU) and on a graphics processing unit (GPU). Results show that an implementation using a straightforward approach can require over 4.5 h to process 15 million base pairs (bps) whereas a properly designed one could perform the same task in less than five minutes. In the best case, a GPU implementation can yield these results in 57 s. The present work shows how parallelism can be used in MATLAB for gene prediction in very large DNA sequences to produce results that are over 270 times faster than a conventional approach. This is significant as MATLAB is typically overlooked due to its apparent slow processing time even though it offers a convenient environment for bioinformatics. From a practical standpoint, this work proposes two strategies for accelerating genome data processing which rely on different parallelization mechanisms. Using a CPU, the work shows that direct access to the MEX function increases execution speed and that the PARFOR construct should be used in order to take full advantage of the parallelizable Goertzel implementation. When the target is a GPU, the work shows that data needs to be segmented into manageable sizes within the GFOR construct before processing in order to minimize execution time.

A suite of MATLAB-based computational tools for automated analysis of COPAS Biosort data

Science.gov (United States)

Morton, Elizabeth; Lamitina, Todd

2010-01-01

Complex Object Parametric Analyzer and Sorter (COPAS) devices are large-object, fluorescence-capable flow cytometers used for high-throughput analysis of live model organisms, including Drosophila melanogaster, Caenorhabditis elegans, and zebrafish. The COPAS is especially useful in C. elegans high-throughput genome-wide RNA interference (RNAi) screens that utilize fluorescent reporters. However, analysis of data from such screens is relatively labor-intensive and time-consuming. Currently, there are no computational tools available to facilitate high-throughput analysis of COPAS data. We used MATLAB to develop algorithms (COPAquant, COPAmulti, and COPAcompare) to analyze different types of COPAS data. COPAquant reads single-sample files, filters and extracts values and value ratios for each file, and then returns a summary of the data. COPAmulti reads 96-well autosampling files generated with the ReFLX adapter, performs sample filtering, graphs features across both wells and plates, performs some common statistical measures for hit identification, and outputs results in graphical formats. COPAcompare performs a correlation analysis between replicate 96-well plates. For many parameters, thresholds may be defined through a simple graphical user interface (GUI), allowing our algorithms to meet a variety of screening applications. In a screen for regulators of stress-inducible GFP expression, COPAquant dramatically accelerated data analysis and allowed us to rapidly move from raw data to hit identification. Because the COPAS file structure is standardized and our MATLAB code is freely available, our algorithms should be extremely useful for analysis of COPAS data from multiple platforms and organisms. The MATLAB code is freely available at our web site (www.med.upenn.edu/lamitinalab/downloads.shtml). PMID:20569218

An algorithm developed in Matlab for the automatic selection of cut-off frequencies, in the correction of strong motion data

Science.gov (United States)

Sakkas, Georgios; Sakellariou, Nikolaos

2018-05-01

Strong motion recordings are the key in many earthquake engineering applications and are also fundamental for seismic design. The present study focuses on the automated correction of accelerograms, analog and digital. The main feature of the proposed algorithm is the automatic selection for the cut-off frequencies based on a minimum spectral value in a predefined frequency bandwidth, instead of the typical signal-to-noise approach. The algorithm follows the basic steps of the correction procedure (instrument correction, baseline correction and appropriate filtering). Besides the corrected time histories, Peak Ground Acceleration, Peak Ground Velocity, Peak Ground Displacement values and the corrected Fourier Spectra are also calculated as well as the response spectra. The algorithm is written in Matlab environment, is fast enough and can be used for batch processing or in real-time applications. In addition, the possibility to also perform a signal-to-noise ratio is added as well as to perform causal or acausal filtering. The algorithm has been tested in six significant earthquakes (Kozani-Grevena 1995, Aigio 1995, Athens 1999, Lefkada 2003 and Kefalonia 2014) of the Greek territory with analog and digital accelerograms.

Comparison 3 - 386 MATLAB

DEFF Research Database (Denmark)

Jensen, Niels

1992-01-01

MATLAB is a C-based general tool for mathematical and engineering calculations with limited capabilities for simulation of non-linear equation systems.......MATLAB is a C-based general tool for mathematical and engineering calculations with limited capabilities for simulation of non-linear equation systems....

MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

Science.gov (United States)

Valdes-Abellan, Javier; Pachepsky, Yakov; Martinez, Gonzalo

2018-01-01

Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.

Low cost MATLAB-based pulse oximeter for deployment in research and development applications.

Science.gov (United States)

Shokouhian, M; Morling, R C S; Kale, I

2013-01-01

Problems such as motion artifact and effects of ambient lights have forced developers to design different signal processing techniques and algorithms to increase the reliability and accuracy of the conventional pulse oximeter device. To evaluate the robustness of these techniques, they are applied either to recorded data or are implemented on chip to be applied to real-time data. Recorded data is the most common method of evaluating however it is not as reliable as real-time measurements. On the other hand, hardware implementation can be both expensive and time consuming. This paper presents a low cost MATLAB-based pulse oximeter that can be used for rapid evaluation of newly developed signal processing techniques and algorithms. Flexibility to apply different signal processing techniques, providing both processed and unprocessed data along with low implementation cost are the important features of this design which makes it ideal for research and development purposes, as well as commercial, hospital and healthcare application.

Practical image and video processing using MATLAB

CERN Document Server

Marques, Oge

2011-01-01

"The book provides a practical introduction to the most important topics in image and video processing using MATLAB (and its Image Processing Toolbox) as a tool to demonstrate the most important techniques and algorithms. The contents are presented in a clear, technically accurate, objective way, with just enough mathematical detail. Most of the chapters are supported by figures, examples, illustrative problems, MATLAB scripts, suggestions for further reading, bibliographical references, useful Web sites, and exercises and computer projects to extend the understanding of their contents"--

Novel algorithm and MATLAB-based program for automated power law analysis of single particle, time-dependent mean-square displacement

Science.gov (United States)

Umansky, Moti; Weihs, Daphne

2012-08-01

In many physical and biophysical studies, single-particle tracking is utilized to reveal interactions, diffusion coefficients, active modes of driving motion, dynamic local structure, micromechanics, and microrheology. The basic analysis applied to those data is to determine the time-dependent mean-square displacement (MSD) of particle trajectories and perform time- and ensemble-averaging of similar motions. The motion of particles typically exhibits time-dependent power-law scaling, and only trajectories with qualitatively and quantitatively comparable MSD should be ensembled. Ensemble averaging trajectories that arise from different mechanisms, e.g., actively driven and diffusive, is incorrect and can result inaccurate correlations between structure, mechanics, and activity. We have developed an algorithm to automatically and accurately determine power-law scaling of experimentally measured single-particle MSD. Trajectories can then categorized and grouped according to user defined cutoffs of time, amplitudes, scaling exponent values, or combinations. Power-law fits are then provided for each trajectory alongside categorized groups of trajectories, histograms of power laws, and the ensemble-averaged MSD of each group. The codes are designed to be easily incorporated into existing user codes. We expect that this algorithm and program will be invaluable to anyone performing single-particle tracking, be it in physical or biophysical systems. Catalogue identifier: AEMD_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMD_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 25 892 No. of bytes in distributed program, including test data, etc.: 5 572 780 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.11 (2010b) or higher, program

Inverse synthetic aperture radar imaging principles, algorithms and applications

CERN Document Server

Chen , Victor C

2014-01-01

Inverse Synthetic Aperture Radar Imaging: Principles, Algorithms and Applications is based on the latest research on ISAR imaging of moving targets and non-cooperative target recognition (NCTR). With a focus on the advances and applications, this book will provide readers with a working knowledge on various algorithms of ISAR imaging of targets and implementation with MATLAB. These MATLAB algorithms will prove useful in order to visualize and manipulate some simulated ISAR images.

Modeling and inversion Matlab algorithms for resistivity, induced polarization and seismic data

Science.gov (United States)

Karaoulis, M.; Revil, A.; Minsley, B. J.; Werkema, D. D.

2011-12-01

M. Karaoulis (1), D.D. Werkema (3), A. Revil (1,2), A., B. Minsley (4), (1) Colorado School of Mines, Dept. of Geophysics, Golden, CO, USA. (2) ISTerre, CNRS, UMR 5559, Université de Savoie, Equipe Volcan, Le Bourget du Lac, France. (3) U.S. EPA, ORD, NERL, ESD, CMB, Las Vegas, Nevada, USA . (4) USGS, Federal Center, Lakewood, 10, 80225-0046, CO. Abstract We propose 2D and 3D forward modeling and inversion package for DC resistivity, time domain induced polarization (IP), frequency-domain IP, and seismic refraction data. For the resistivity and IP case, discretization is based on rectangular cells, where each cell has as unknown resistivity in the case of DC modelling, resistivity and chargeability in the time domain IP modelling, and complex resistivity in the spectral IP modelling. The governing partial-differential equations are solved with the finite element method, which can be applied to both real and complex variables that are solved for. For the seismic case, forward modeling is based on solving the eikonal equation using a second-order fast marching method. The wavepaths are materialized by Fresnel volumes rather than by conventional rays. This approach accounts for complicated velocity models and is advantageous because it considers frequency effects on the velocity resolution. The inversion can accommodate data at a single time step, or as a time-lapse dataset if the geophysical data are gathered for monitoring purposes. The aim of time-lapse inversion is to find the change in the velocities or resistivities of each model cell as a function of time. Different time-lapse algorithms can be applied such as independent inversion, difference inversion, 4D inversion, and 4D active time constraint inversion. The forward algorithms are benchmarked against analytical solutions and inversion results are compared with existing ones. The algorithms are packaged as Matlab codes with a simple Graphical User Interface. Although the code is parallelized for multi

PAPR Reduction in OFDM-based Visible Light Communication Systems Using a Combination of Novel Peak-value Feedback Algorithm and Genetic Algorithm

Science.gov (United States)

Deng, Honggui; Liu, Yan; Ren, Shuang; He, Hailang; Tang, Chengying

2017-10-01

We propose an enhanced partial transmit sequence technique based on novel peak-value feedback algorithm and genetic algorithm (GAPFA-PTS) to reduce peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals in visible light communication (VLC) systems(VLC-OFDM). To demonstrate the advantages of our proposed algorithm, we analyze the flow of proposed technique and compare the performances with other techniques through MATLAB simulation. The results show that GAPFA-PTS technique achieves a significant improvement in PAPR reduction while maintaining low bit error rate (BER) and low complexity in VLC-OFDM systems.

Instruction of pattern recognition by MATLAB practice 1

International Nuclear Information System (INIS)

1999-06-01

This book describes the pattern recognition by MATLAB practice. It includes possibility and limit of AI, introduction of pattern recognition a vector and matrix, basic status and a probability theory, a random variable and probability distribution, statistical decision theory, data-mining, gaussian mixture model, a nerve cell modeling such as Hebb's learning rule, LMS learning rule, genetic algorithm, dynamic programming and DTW, HMN on Markov model and HMM's three problems and solution, introduction of SVM with KKT condition and margin optimum, kernel trick and MATLAB practice.

Implementation and Comparison of the Lifting 5/3 and 9/7 Algorithms in MatLab on GPU

Directory of Open Access Journals (Sweden)

Randa Khemiri

2016-06-01

Full Text Available In order to accelerate the Discrete Wavelet Transform DWT, we have implemented and compared the lifting "Le Gall5/3" and "Cohen-Daubechies-Feauveau9/7" (CDF9/7 algorithms on a low cost NVIDIA’s GPU. The suggested implementation is realized in MatLab using the in-house parallel computation toolbox (PCT. Our experimental results indicate, that the speedup is proportional to the image size until it attains a maximum at 20482 pixels, beyond these values the curve decreases. The performance with GPU enhances above a factor of 2~3 compared with CPU.

Study of a photovoltaic system with MPPT using Matlab

Directory of Open Access Journals (Sweden)

Dumitru Pop

2012-12-01

Full Text Available In this paper a photovoltaic (PV system is analyzed using Matlab. First, a Matlab code is written in order to obtain the I-V and P-V curves at different values of solar irradiation and cell temperature. The results were compared with the experimental data of a commercial PV module, USP 150. Then, the code was implemented in Simulink and, along with a MPPT algorithm and a DC-DC converter, the whole system was simulated.

OXlearn: a new MATLAB-based simulation tool for connectionist models.

Science.gov (United States)

Ruh, Nicolas; Westermann, Gert

2009-11-01

OXlearn is a free, platform-independent MATLAB toolbox in which standard connectionist neural network models can be set up, run, and analyzed by means of a user-friendly graphical interface. Due to its seamless integration with the MATLAB programming environment, the inner workings of the simulation tool can be easily inspected and/or extended using native MATLAB commands or components. This combination of usability, transparency, and extendability makes OXlearn an efficient tool for the implementation of basic research projects or the prototyping of more complex research endeavors, as well as for teaching. Both the MATLAB toolbox and a compiled version that does not require access to MATLAB can be downloaded from http://psych.brookes.ac.uk/oxlearn/.

Statistics in Matlab a primer

CERN Document Server

Cho, MoonJung

2014-01-01

List of Tables Preface MATLAB BasicsDesktop Environment Getting Help and Other Documentation Data Import and Export Data I/O via the Command Line The Import Wizard Examples of Data I/O in MATLAB Data I/O with the Statistics Toolbox More Functions for Data I/O Data in MATLAB Data Objects in Base MATLAB Accessing Data Elements Examples of Joining Data Sets Data Types in the Statistics Toolbox Object-Oriented Programming Miscellaneous Topics File and Workspace Management Punctuation in MATLAB Arithmetic Operators Functions in MATLAB Summary and Further Reading Visualizing DataBasic Plot Functions Plotting 2-D Data Plotting 3-D Data Examples Scatter Plots Basic 2-D and 3-D Scatter Plots Scatter Plot Matrix Examples GUIs for Graphics Simple Plot Editing Plotting Tools Interface PLOTS Tab Summary and Further Reading Descriptive StatisticsMeasures of Location Means, Medians, and Modes Examples Measures of Dispersion Range Variance and Standard Deviation Covariance and Correlation Examples Describing the Distribution...

MATLAB - Introduction

International Nuclear Information System (INIS)

Jung, Heon Seul

2005-08-01

This book introduces MATLAB giving descriptions of analysis and design of this control system like what is control? cases of control system, working environment of MATLAB, signs of MATLAB, commands of MATLAB, and drawing graphs. It also tells of basic use of simulink, mathematical model of physical system like mechanical-electrical analogous system, system analysis in time part, frequency analysis, state space and design such as canonical from and principle of duality and state observer design.

A feature extraction algorithm based on corner and spots in self-driving vehicles

Directory of Open Access Journals (Sweden)

Yupeng FENG

2017-06-01

Full Text Available To solve the poor real-time performance problem of the visual odometry based on embedded system with limited computing resources, an image matching method based on Harris and SIFT is proposed, namely the Harris-SIFT algorithm. On the basis of the review of SIFT algorithm, the principle of Harris-SIFT algorithm is provided. First, Harris algorithm is used to extract the corners of the image as candidate feature points, and scale invariant feature transform (SIFT features are extracted from those candidate feature points. At last, through an example, the algorithm is simulated by Matlab, then the complexity and other performance of the algorithm are analyzed. The experimental results show that the proposed method reduces the computational complexity and improves the speed of feature extraction. Harris-SIFT algorithm can be used in the real-time vision odometer system, and will bring about a wide application of visual odometry in embedded navigation system.

Matlab for dummies

CERN Document Server

Sizemore, Jim

2014-01-01

Plot graphs, solve equations, and write code in a flash! If you work in a STEM field, chances are you'll be using MATLAB on a daily basis. MATLAB is a popular and powerful computational tool and this book provides everything you need to start manipulating and plotting your data. MATLAB has rapidly become the premier data tool, and MATLAB For Dummies is a comprehensive guide to the fundamentals. MATLAB For Dummies guides you through this complex computational language from installation to visualization to automation.Learn MATLAB's language fundamentals including syntax, operators, and data type

Embedded algorithms within an FPGA-based system to process nonlinear time series data

Science.gov (United States)

Jones, Jonathan D.; Pei, Jin-Song; Tull, Monte P.

2008-03-01

This paper presents some preliminary results of an ongoing project. A pattern classification algorithm is being developed and embedded into a Field-Programmable Gate Array (FPGA) and microprocessor-based data processing core in this project. The goal is to enable and optimize the functionality of onboard data processing of nonlinear, nonstationary data for smart wireless sensing in structural health monitoring. Compared with traditional microprocessor-based systems, fast growing FPGA technology offers a more powerful, efficient, and flexible hardware platform including on-site (field-programmable) reconfiguration capability of hardware. An existing nonlinear identification algorithm is used as the baseline in this study. The implementation within a hardware-based system is presented in this paper, detailing the design requirements, validation, tradeoffs, optimization, and challenges in embedding this algorithm. An off-the-shelf high-level abstraction tool along with the Matlab/Simulink environment is utilized to program the FPGA, rather than coding the hardware description language (HDL) manually. The implementation is validated by comparing the simulation results with those from Matlab. In particular, the Hilbert Transform is embedded into the FPGA hardware and applied to the baseline algorithm as the centerpiece in processing nonlinear time histories and extracting instantaneous features of nonstationary dynamic data. The selection of proper numerical methods for the hardware execution of the selected identification algorithm and consideration of the fixed-point representation are elaborated. Other challenges include the issues of the timing in the hardware execution cycle of the design, resource consumption, approximation accuracy, and user flexibility of input data types limited by the simplicity of this preliminary design. Future work includes making an FPGA and microprocessor operate together to embed a further developed algorithm that yields better

DSISoft—a MATLAB VSP data processing package

Science.gov (United States)

Beaty, K. S.; Perron, G.; Kay, I.; Adam, E.

2002-05-01

DSISoft is a public domain vertical seismic profile processing software package developed at the Geological Survey of Canada. DSISoft runs under MATLAB version 5.0 and above and hence is portable between computer operating systems supported by MATLAB (i.e. Unix, Windows, Macintosh, Linux). The package includes processing modules for reading and writing various standard seismic data formats, performing data editing, sorting, filtering, and other basic processing modules. The processing sequence can be scripted allowing batch processing and easy documentation. A structured format has been developed to ensure future additions to the package are compatible with existing modules. Interactive modules have been created using MATLAB's graphical user interface builder for displaying seismic data, picking first break times, examining frequency spectra, doing f- k filtering, and plotting the trace header information. DSISoft modular design facilitates the incorporation of new processing algorithms as they are developed. This paper gives an overview of the scope of the software and serves as a guide for the addition of new modules.

Risk Assessment for Bridges Safety Management during Operation Based on Fuzzy Clustering Algorithm

Directory of Open Access Journals (Sweden)

Xia Hanyu

2016-01-01

Full Text Available In recent years, large span and large sea-crossing bridges are built, bridges accidents caused by improper operational management occur frequently. In order to explore the better methods for risk assessment of the bridges operation departments, the method based on fuzzy clustering algorithm is selected. Then, the implementation steps of fuzzy clustering algorithm are described, the risk evaluation system is built, and Taizhou Bridge is selected as an example, the quantitation of risk factors is described. After that, the clustering algorithm based on fuzzy equivalence is calculated on MATLAB 2010a. In the last, Taizhou Bridge operation management departments are classified and sorted according to the degree of risk, and the safety situation of operation departments is analyzed.

MATLAB syntaksen

DEFF Research Database (Denmark)

Skajaa, Anders; Jørgensen, Jakob Heide

MATLAB er et matematik-program som fokuserer på anvendelsen af matricer og vektorer. Deraf navnet MATrix LABoratory. Denne bog er en praktisk vejledning i at forstår og anvende MATLAB syntaksen og fungerer som en hurtig genvej til dig, der skal i gang med at anvende MATLAB i forbindelse med fx dit...

Algorithm 873: LSTRS: MATLAB Software for Large-Scale Trust-Region Subproblems and Regularization

DEFF Research Database (Denmark)

Rojas Larrazabal, Marielba de la Caridad; Santos, Sandra A.; Sorensen, Danny C.

2008-01-01

A MATLAB 6.0 implementation of the LSTRS method is resented. LSTRS was described in Rojas, M., Santos, S.A., and Sorensen, D.C., A new matrix-free method for the large-scale trust-region subproblem, SIAM J. Optim., 11(3):611-646, 2000. LSTRS is designed for large-scale quadratic problems with one...... at each step. LSTRS relies on matrix-vector products only and has low and fixed storage requirements, features that make it suitable for large-scale computations. In the MATLAB implementation, the Hessian matrix of the quadratic objective function can be specified either explicitly, or in the form...... of a matrix-vector multiplication routine. Therefore, the implementation preserves the matrix-free nature of the method. A description of the LSTRS method and of the MATLAB software, version 1.2, is presented. Comparisons with other techniques and applications of the method are also included. A guide...

A Genetic-Algorithms-Based Approach for Programming Linear and Quadratic Optimization Problems with Uncertainty

Directory of Open Access Journals (Sweden)

Weihua Jin

2013-01-01

Full Text Available This paper proposes a genetic-algorithms-based approach as an all-purpose problem-solving method for operation programming problems under uncertainty. The proposed method was applied for management of a municipal solid waste treatment system. Compared to the traditional interactive binary analysis, this approach has fewer limitations and is able to reduce the complexity in solving the inexact linear programming problems and inexact quadratic programming problems. The implementation of this approach was performed using the Genetic Algorithm Solver of MATLAB (trademark of MathWorks. The paper explains the genetic-algorithms-based method and presents details on the computation procedures for each type of inexact operation programming problems. A comparison of the results generated by the proposed method based on genetic algorithms with those produced by the traditional interactive binary analysis method is also presented.

Speeding up the MATLAB complex networks package using graphic processors

International Nuclear Information System (INIS)

Zhang Bai-Da; Wu Jun-Jie; Li Xin; Tang Yu-Hua

2011-01-01

The availability of computers and communication networks allows us to gather and analyse data on a far larger scale than previously. At present, it is believed that statistics is a suitable method to analyse networks with millions, or more, of vertices. The MATLAB language, with its mass of statistical functions, is a good choice to rapidly realize an algorithm prototype of complex networks. The performance of the MATLAB codes can be further improved by using graphic processor units (GPU). This paper presents the strategies and performance of the GPU implementation of a complex networks package, and the Jacket toolbox of MATLAB is used. Compared with some commercially available CPU implementations, GPU can achieve a speedup of, on average, 11.3×. The experimental result proves that the GPU platform combined with the MATLAB language is a good combination for complex network research. (interdisciplinary physics and related areas of science and technology)

MATLAB based beam orbit correction system of HLS storage ring

International Nuclear Information System (INIS)

Ding Shichuan; Liu Gongfa; Xuan Ke; Li Weimin; Wang Lin; Wang Jigang; Li Chuan; Bao Xun; Guo Weiqun

2006-01-01

The distortion of closed orbit usually causes much side effect which is harmful to synchrotron radiation source such as HLS, so it is necessary to correct the distortion of closed orbit. In this paper, the correction principle, development procedure and test of MATLAB based on beam orbit correction system of HLS storage ring are described. The correction system is consisted of the beam orbit measure system, corrector magnet system and the control system, and the beam orbit correction code based on MATLAB is working on the operation interface. The data of the beam orbit are analyzed and calculated firstly, and then the orbit is corrected by changing corrector strength via control system. The test shows that the distortion of closed orbit is from max 4.468 mm before correction to max 0.299 mm after correction as well as SDEV is from 2.986 mm to 0.087 mm. So the correction system reaches the design goal. (authors)

A Biometric Face Recognition System Using an Algorithm Based on the Principal Component Analysis Technique

Directory of Open Access Journals (Sweden)

Gheorghe Gîlcă

2015-06-01

Full Text Available This article deals with a recognition system using an algorithm based on the Principal Component Analysis (PCA technique. The recognition system consists only of a PC and an integrated video camera. The algorithm is developed in MATLAB language and calculates the eigenfaces considered as features of the face. The PCA technique is based on the matching between the facial test image and the training prototype vectors. The mathcing score between the facial test image and the training prototype vectors is calculated between their coefficient vectors. If the matching is high, we have the best recognition. The results of the algorithm based on the PCA technique are very good, even if the person looks from one side at the video camera.

An Accelerator Control Middle Layer Using MATLAB

International Nuclear Information System (INIS)

Portmann, Gregory J.; Corbett, Jeff; Terebilo, Andrei

2005-01-01

Matlab is an interpretive programming language originally developed for convenient use with the LINPACK and EISPACK libraries. Matlab is appealing for accelerator physics because it is matrix-oriented, provides an active workspace for system variables, powerful graphics capabilities, built-in math libraries, and platform independence. A number of accelerator software toolboxes have been written in Matlab -- the Accelerator Toolbox (AT) for model-based machine simulations, LOCO for on-line model calibration, and Matlab Channel Access (MCA) to connect with EPICS. The function of the MATLAB ''MiddleLayer'' is to provide a scripting language for machine simulations and on-line control, including non-EPICS based control systems. The MiddleLayer has simplified and streamlined development of high-level applications including configuration control, energy ramp, orbit correction, photon beam steering, ID compensation, beam-based alignment, tune correction and response matrix measurement. The database-driven Middle Layer software is largely machine-independent and easy to port. Six accelerators presently use the software package with more scheduled to come on line soon

Towards heterogeneous robot team path planning: acquisition of multiple routes with a modified spline-based algorithm

Directory of Open Access Journals (Sweden)

Lavrenov Roman

2017-01-01

Full Text Available Our research focuses on operation of a heterogeneous robotic group that carries out point-to point navigation in GPS-denied dynamic environment, applying a combined local and global planning approach. In this paper, we introduce a homotopy-based high-level planner, which uses a modified splinebased path-planning algorithm. The algorithm utilizes Voronoi graph for global planning and a set of optimization criteria for local improvements of selected paths. The simulation was implemented in Matlab environment.

Using MATLAB software with Tomcat server and Java platform for remote image analysis in pathology.

Science.gov (United States)

Markiewicz, Tomasz

2011-03-30

The Matlab software is a one of the most advanced development tool for application in engineering practice. From our point of view the most important is the image processing toolbox, offering many built-in functions, including mathematical morphology, and implementation of a many artificial neural networks as AI. It is very popular platform for creation of the specialized program for image analysis, also in pathology. Based on the latest version of Matlab Builder Java toolbox, it is possible to create the software, serving as a remote system for image analysis in pathology via internet communication. The internet platform can be realized based on Java Servlet Pages with Tomcat server as servlet container. In presented software implementation we propose remote image analysis realized by Matlab algorithms. These algorithms can be compiled to executable jar file with the help of Matlab Builder Java toolbox. The Matlab function must be declared with the set of input data, output structure with numerical results and Matlab web figure. Any function prepared in that manner can be used as a Java function in Java Servlet Pages (JSP). The graphical user interface providing the input data and displaying the results (also in graphical form) must be implemented in JSP. Additionally the data storage to database can be implemented within algorithm written in Matlab with the help of Matlab Database Toolbox directly with the image processing. The complete JSP page can be run by Tomcat server. The proposed tool for remote image analysis was tested on the Computerized Analysis of Medical Images (CAMI) software developed by author. The user provides image and case information (diagnosis, staining, image parameter etc.). When analysis is initialized, input data with image are sent to servlet on Tomcat. When analysis is done, client obtains the graphical results as an image with marked recognized cells and also the quantitative output. Additionally, the results are stored in a server

Pareto design of state feedback tracking control of a biped robot via multiobjective PSO in comparison with sigma method and genetic algorithms: modified NSGAII and MATLAB's toolbox.

Science.gov (United States)

Mahmoodabadi, M J; Taherkhorsandi, M; Bagheri, A

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot.

Fast compact algorithms and software for spline smoothing

CERN Document Server

Weinert, Howard L

2012-01-01

Fast Compact Algorithms and Software for Spline Smoothing investigates algorithmic alternatives for computing cubic smoothing splines when the amount of smoothing is determined automatically by minimizing the generalized cross-validation score. These algorithms are based on Cholesky factorization, QR factorization, or the fast Fourier transform. All algorithms are implemented in MATLAB and are compared based on speed, memory use, and accuracy. An overall best algorithm is identified, which allows very large data sets to be processed quickly on a personal computer.

Radar signal analysis and processing using Matlab

CERN Document Server

Mahafza, Bassem R

2008-01-01

Offering radar-related software for the analysis and design of radar waveform and signal processing, this book provides comprehensive coverage of radar signals and signal processing techniques and algorithms. It contains numerous graphical plots, common radar-related functions, table format outputs, and end-of-chapter problems. The complete set of MATLAB[registered] functions and routines are available for download online.

Optimal Design for PID Controller Based on DE Algorithm in Omnidirectional Mobile Robot

Directory of Open Access Journals (Sweden)

Wu Peizhang

2017-01-01

Full Text Available This paper introduces a omnidirectional mobile robot based on Mecanum wheel, which is used for conveying heavy load in a small space of the automatic warehousing logistics center. Then analyzes and establishes the omnidirectional chassis inverse and forward kinematic model. In order to improve the performance of motion, the paper proposes the optimal PID controller based on differential evolution algorithm. Finally, through MATLAB simulation, the results show that the kinematic model of mobile robot chassis is correct, further more the controller optimized by the DE algorithm working better than the traditional Z-N PID tuned. So the optimal scheme is reasonable and feasible, which has a value for engineering applications.

Forecasting Jakarta composite index (IHSG) based on chen fuzzy time series and firefly clustering algorithm

Science.gov (United States)

Ningrum, R. W.; Surarso, B.; Farikhin; Safarudin, Y. M.

2018-03-01

This paper proposes the combination of Firefly Algorithm (FA) and Chen Fuzzy Time Series Forecasting. Most of the existing fuzzy forecasting methods based on fuzzy time series use the static length of intervals. Therefore, we apply an artificial intelligence, i.e., Firefly Algorithm (FA) to set non-stationary length of intervals for each cluster on Chen Method. The method is evaluated by applying on the Jakarta Composite Index (IHSG) and compare with classical Chen Fuzzy Time Series Forecasting. Its performance verified through simulation using Matlab.

A Study Regarding the Generalization Capacity of ‎Image Classification by Using Neuroal Networks In ‎Matlab

Directory of Open Access Journals (Sweden)

Evan Madhi Al Rubaie

2018-02-01

Full Text Available The paper performs an algorithmic and experimental study regarding the generalization capacity of the scheme based on neuronal networks for the recognition of new images of the face. This enables both a rendering of graphic representations and the classification of image classes in Matlab. The purpose is to describe the recognition algorithm, to project and implement an application which proposes both the graphic representation of the images used by the neuronal training algorithm but also the implementation of the perceptron neuronal algorithm and the determination of the generalization capacity of the separating hyper plane of the considered image classes

MATLAB-Based Program for Teaching Autocorrelation Function and Noise Concepts

Science.gov (United States)

Jovanovic Dolecek, G.

2012-01-01

An attractive MATLAB-based tool for teaching the basics of autocorrelation function and noise concepts is presented in this paper. This tool enhances traditional in-classroom lecturing. The demonstrations of the tool described here highlight the description of the autocorrelation function (ACF) in a general case for wide-sense stationary (WSS)…

MatLab script to C code converter for embedded processors of FLASH LLRF control system

Science.gov (United States)

Bujnowski, K.; Siemionczyk, A.; Pucyk, P.; Szewiński, J.; Pożniak, K. T.; Romaniuk, R. S.

2008-01-01

The low level RF control system (LLRF) of FEL serves for stabilization of the electromagnetic (EM) field in the superconducting niobium, resonant, microwave cavities and for controlling high power (MW) klystron. LLRF system of FLASH accelerator bases on FPGA technology and embedded microprocessors. Basic and auxiliary functions of the systems are listed as well as used algorithms for superconductive cavity parameters identification. These algorithms were prepared originally in Matlab. The main part of the paper presents implementation of the cavity parameters identification algorithm in a PowerPC processor embedded in the FPGA circuit VirtexIIPro. A construction of a very compact Matlab script converter to C code was presented, referred to as M2C. The application is designed specifically for embedded systems of very confined resources. The generated code is optimized for the weight. The code should be transferable between different hardware platforms. The converter generates a code for Linux and for stand-alone applications. Functional structure of the program was described and the way it is acting. FLEX and BIZON tools were used for construction of the converter. The paper concludes with an example of the M2C application to convert a complex identification algorithm for superconductive cavities in FLASH laser.

The Matlab Syntax

DEFF Research Database (Denmark)

Jørgensen, Jakob Heide; Skajaa, Anders

Matlab (MATrix LABoratory) is one of the most widely used programming environments for numerical computations and simulations in the technical sciences. The reason is that Matlab makes it easy to get started as well as to construct advanced programs. This book is a practical guide to understanding...... and using Matlab. It works as a quick reference for anyone who is starting to use Matlab for example while enrolled in university studies. For this reason, the book is limited to covering what is typically used by a university student and is designed as a reference of the syntax including plenty of examples....... While the primary audience of the book is university students, it is well suited for anyone who wants to become acquainted with Matlab....

Problem-based learning in communication systems using MATLAB and Simulink

CERN Document Server

Choi, Kwonhue

2016-01-01

Designed to help teach and understand communication systems using a classroom-tested, active learning approach. This book covers the basic concepts of signals, and analog and digital communications, to more complex simulations in communication systems. Problem-Based Learning in Communication Systems Using MATLAB and Simulink begins by introducing MATLAB and Simulink to prepare readers who are unfamiliar with these environments in order to tackle projects and exercises included in this book. Discussions on simulation of signals, filter design, sampling and reconstruction, and analog communications are covered next. The book concludes by covering advanced topics such as Viterbi decoding, OFDM and MIMO. In addition, this book contains examples of how to convert waveforms, constructed in simulation, into electric signals. It also includes problems illustrating how to complete actual wireless communications in the band near ultrasonic frequencies. A content-m pping table is included in this book to help instruc...

Numerical methods in finance and economics a MATLAB-based introduction

CERN Document Server

Brandimarte, Paolo

2006-01-01

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of financeThe use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB?-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB?--the powerful numerical computing environment--for financial applications.The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions.Among this book''s most outstanding features is the...

Accelerator Modeling with MATLAB Accelerator Toolbox

International Nuclear Information System (INIS)

2002-01-01

This paper introduces Accelerator Toolbox (AT)--a collection of tools to model storage rings and beam transport lines in the MATLAB environment. The objective is to illustrate the flexibility and efficiency of the AT-MATLAB framework. The paper discusses three examples of problems that are analyzed frequently in connection with ring-based synchrotron light sources

A Matlab/Simulink-Based Interactive Module for Servo Systems Learning

Science.gov (United States)

Aliane, N.

2010-01-01

This paper presents an interactive module for learning both the fundamental and practical issues of servo systems. This module, developed using Simulink in conjunction with the Matlab graphical user interface (Matlab-GUI) tool, is used to supplement conventional lectures in control engineering and robotics subjects. First, the paper introduces the…

Collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation

Science.gov (United States)

Yang, Shangwen; Guo, Baohua; Xiao, Xuefei; Gao, Haichao

2018-01-01

To allocate the en-routes and slots to the flights with collaborative decision making, a collaborative en-route and slot allocation algorithm based on fuzzy comprehensive evaluation was proposed. Evaluation indexes include flight delay costs, delay time and the number of turning points. Analytic hierarchy process is applied to determining index weights. Remark set for current two flights not yet obtained the en-route and slot in flight schedule is established. Then, fuzzy comprehensive evaluation is performed, and the en-route and slot for the current two flights are determined. Continue selecting the flight not yet obtained an en-route and a slot in flight schedule. Perform fuzzy comprehensive evaluation until all flights have obtained the en-routes and slots. MatlabR2007b was applied to numerical test based on the simulated data of a civil en-route. Test results show that, compared with the traditional strategy of first come first service, the algorithm gains better effect. The effectiveness of the algorithm was verified.

Application of MATLAB in testing digital power supply controllers

International Nuclear Information System (INIS)

Ke Xinhua; Chinese Academy of Sciences, Beijing; Lu Songlin; Shen Tianjian

2008-01-01

Based on introducing MATLAB SISOTOOL in MATLAB control box and the magnet power supply system in detail, this paper presented the application of MATLAB SISOTOOL in Testing Digital Power Supply controllers. This control tool should be popularized because of its characteristics of convenience and easy-to-use. (authors)

Basis and application of MATLAB

International Nuclear Information System (INIS)

Shin, Chun Sik; An, Yeong Ju; Byun, Gi Sik; Lee, Hyeong Gi

1998-01-01

This book introduces MATLAB, which deals with operation and basic function, MATLAB programming like for, if, else, while and script file, equation, calculation and interpolation, operation of the matrix, file management function, such as basic file management function input-output of internal file of MATLAB input-output of outer file of MATLAB, basic graph function, two-dimensional graph and three-dimensional graph and other graph function debugger of MATLAB program in 4.2 version and debugger of MATLAB in 5.1 version.

Matlab-Based Modeling and Simulations to Study the Performance of Different MPPT Techniques Used for Photovoltaic Systems under Partially Shaded Conditions

Directory of Open Access Journals (Sweden)

Jehun Hahm

2015-01-01

Full Text Available A pulse-width-modulator- (PWM- based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT used in photovoltaic (PV systems. Under partially shaded conditions and temperature, PV array characteristics become more complex, with multiple power-voltage maxima. MPPT is an automatic control technique to adjust power interfaces and deliver power for a diverse range of insolation values, temperatures, and partially shaded modules. The PV system is tested using two conventional algorithms: the Perturb and Observe (P&O algorithm and the Incremental Conductance (IncCond algorithm, which are simple to implement for a PV array. The proposed method applied a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under nonuniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The PWM-based sliding mode controller successfully overcomes the issues presented by nonuniform conditions and tracks the global MPP. In this paper, the PV system consists of a solar module under shade connected to a boost converter that is controlled by three different algorithms and is generated using Matlab/Simulink.

The method in γ spectrum analysis with artificial neural network based on MATLAB

International Nuclear Information System (INIS)

Bai Lixin; Zhang Yiyun; Xu Jiayun; Wu Liping

2003-01-01

Analyzing γ spectrum with artificial neural network have the advantage of using the information of whole spectrum and having high analyzing precision. A convenient realization based on MATLAB was present in this

The Application of PSIM & Matlab/ Simulink in Teaching of Power Electronics Courses

Directory of Open Access Journals (Sweden)

Sameer Hanna Khader

2011-07-01

Full Text Available This paper presents a comparison analysis between two engineering software platforms, Matlab/Simulink & PSIM, which are used as major educational tools in teaching of power electronics and electrical drive courses, in additional to conducted research in these fields. The comparison analysis is based on studying the design simplicity of the module, time consumed in building of the module, accuracy, functionality, simulation time, and the acceptability of obtained results. Various power electronic simulation circuits are illustrated and the results are processed and displayed. The simulation results states that Matlab/Simulink is a suitable platform for control and regulation of simulation processes, in additional to its dominant role in conducting research tasks. Conversely, PSIM is dedicated to power electronic circuits and machine simulation tasks with fast and robust algorithms and suitable for educational purposes. It is recommended that both packages can be used in teaching power electronics courses.

New Technique for Voltage Tracking Control of a Boost Converter Based on the PSO Algorithm and LTspice

DEFF Research Database (Denmark)

Farhang, Peyman; Drimus, Alin; Mátéfi-Tempfli, Stefan

2015-01-01

In this paper, a new technique is proposed to design a Modified PID (MPID) controller for a Boost converter. An interface between LTspice and MATLAB is carried out to implement the Particle Swarm Optimization (PSO) algorithm. The PSO algorithm which has the appropriate capability to find out...... the optimal solutions is run in MATLAB while it is interfaced with LTspice for simulation of the circuit using actual component models obtained from manufacturers. The PSO is utilized to solve the optimization problem in order to find the optimal parameters of MPID and PID controllers. The performances...

Implementation of Digital Watermarking Using MATLAB Software

OpenAIRE

Karnpriya Vyas; Kirti Sethiya; Sonu Jain

2012-01-01

Digital watermarking holds significant promise as one of the keys to protecting proprietary digital content in the coming years. It focuses on embedding information inside a digital object such that the embedded information is in separable bound to the object. The proposed scheme has been implemented on MATLAB, as it is a high level technical computing language and interactive environment for algorithm development, data visualization, data analysis, and numerical computation. We w...

Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy

International Nuclear Information System (INIS)

Ranganathan, Vaitheeswaran; Sathiya Narayanan, V.K.; Bhangle, Janhavi R.; Gupta, Kamlesh K.; Basu, Sumit; Maiya, Vikram; Joseph, Jolly; Nirhali, Amit

2010-01-01

This study aims to evaluate the performance of a new algorithm for optimization of beam weights in anatomy-based intensity modulated radiotherapy (IMRT). The algorithm uses a numerical technique called Gaussian-Elimination that derives the optimum beam weights in an exact or non-iterative way. The distinct feature of the algorithm is that it takes only fraction of a second to optimize the beam weights, irrespective of the complexity of the given case. The algorithm has been implemented using MATLAB with a Graphical User Interface (GUI) option for convenient specification of dose constraints and penalties to different structures. We have tested the numerical and clinical capabilities of the proposed algorithm in several patient cases in comparison with KonRad inverse planning system. The comparative analysis shows that the algorithm can generate anatomy-based IMRT plans with about 50% reduction in number of MUs and 60% reduction in number of apertures, while producing dose distribution comparable to that of beamlet-based IMRT plans. Hence, it is clearly evident from the study that the proposed algorithm can be effectively used for clinical applications. (author)

The Matlab Radial Basis Function Toolbox

Directory of Open Access Journals (Sweden)

Scott A. Sarra

2017-03-01

Full Text Available Radial Basis Function (RBF methods are important tools for scattered data interpolation and for the solution of Partial Differential Equations in complexly shaped domains. The most straight forward approach used to evaluate the methods involves solving a linear system which is typically poorly conditioned. The Matlab Radial Basis Function toolbox features a regularization method for the ill-conditioned system, extended precision floating point arithmetic, and symmetry exploitation for the purpose of reducing flop counts of the associated numerical linear algebra algorithms.

Flexible missile autopilot design studies with PC-MATLAB/386

Science.gov (United States)

Ruth, Michael J.

1989-01-01

Development of a responsive, high-bandwidth missile autopilot for airframes which have structural modes of unusually low frequency presents a challenging design task. Such systems are viable candidates for modern, state-space control design methods. The PC-MATLAB interactive software package provides an environment well-suited to the development of candidate linear control laws for flexible missile autopilots. The strengths of MATLAB include: (1) exceptionally high speed (MATLAB's version for 80386-based PC's offers benchmarks approaching minicomputer and mainframe performance); (2) ability to handle large design models of several hundred degrees of freedom, if necessary; and (3) broad extensibility through user-defined functions. To characterize MATLAB capabilities, a simplified design example is presented. This involves interactive definition of an observer-based state-space compensator for a flexible missile autopilot design task. MATLAB capabilities and limitations, in the context of this design task, are then summarized.

Matlab for engineers explained

CERN Document Server

Gustafsson, Fredrik

2003-01-01

This book is written for students at bachelor and master programs and has four different purposes, which split the book into four parts: 1. To teach first or early year undergraduate engineering students basic knowledge in technical computations and programming using MATLAB. The first part starts from first principles and is therefore well suited both for readers with prior exposure to MATLAB but lacking a solid foundational knowledge of the capabilities of the system and readers not having any previous experience with MATLAB. The foundational knowledge gained from these interactive guided tours of the system will hopefully be sufficient for an effective utilization of MATLAB in the engineering profession, in education and in research. 2. To explain the foundations of more advanced use of MATLAB using the facilities added the last couple of years, such as extended data structures, object orientation and advanced graphics. 3. To give an introduction to the use of MATLAB in typical undergraduate courses in elec...

An introduction to MATLAB.

Science.gov (United States)

Sobie, Eric A

2011-09-13

This two-part lecture introduces students to the scientific computing language MATLAB. Prior computer programming experience is not required. The lectures present basic concepts of computer programming logic that tend to cause difficulties for beginners in addition to concepts that relate specifically to the MATLAB language syntax. The lectures begin with a discussion of vectors, matrices, and arrays. Because many types of biological data, such as fluorescence images and DNA microarrays, are stored as two-dimensional objects, processing these data is a form of array manipulation, and MATLAB is especially adept at handling such array objects. The students are introduced to basic commands in MATLAB, as well as built-in functions that provide useful shortcuts. The second lecture focuses on the differences between MATLAB scripts and MATLAB functions and describes when one method of programming organization might be preferable to the other. The principles are illustrated through the analysis of experimental data, specifically measurements of intracellular calcium concentration in live cells obtained using confocal microscopy.

Intelligent traffic lights based on MATLAB

Science.gov (United States)

Nie, Ying

2018-04-01

In this paper, I describes the traffic lights system and it has some. Through analysis, I used MATLAB technology, transformed the camera photographs into digital signals. Than divided the road vehicle is into three methods: very congestion, congestion, a little congestion. Through the MCU programming, solved the different roads have different delay time, and Used this method, saving time and resources, so as to reduce road congestion.

On the Evaluation of Computational Results Obtained from Solving System of linear Equations With matlab The Dual affine Scalling interior Point

International Nuclear Information System (INIS)

Murfi, Hendri; Basaruddin, T.

2001-01-01

The interior point method for linear programming has gained extraordinary interest as an alternative to simplex method since Karmarkar presented a polynomial-time algorithm for linear programming based on interior point method. In implementation of the algorithm of this method, there are two important things that have impact heavily to performance of the algorithm; they are data structure and used method to solve linear equation system in the algorithm. This paper describes about solving linear equation system in variants of the algorithm called dual-affine scaling algorithm. Next, we evaluate experimentally results of some used methods, either direct method or iterative method. The experimental evaluation used Matlab

A New Parallel Approach for Accelerating the GPU-Based Execution of Edge Detection Algorithms.

Science.gov (United States)

Emrani, Zahra; Bateni, Soroosh; Rabbani, Hossein

2017-01-01

Real-time image processing is used in a wide variety of applications like those in medical care and industrial processes. This technique in medical care has the ability to display important patient information graphi graphically, which can supplement and help the treatment process. Medical decisions made based on real-time images are more accurate and reliable. According to the recent researches, graphic processing unit (GPU) programming is a useful method for improving the speed and quality of medical image processing and is one of the ways of real-time image processing. Edge detection is an early stage in most of the image processing methods for the extraction of features and object segments from a raw image. The Canny method, Sobel and Prewitt filters, and the Roberts' Cross technique are some examples of edge detection algorithms that are widely used in image processing and machine vision. In this work, these algorithms are implemented using the Compute Unified Device Architecture (CUDA), Open Source Computer Vision (OpenCV), and Matrix Laboratory (MATLAB) platforms. An existing parallel method for Canny approach has been modified further to run in a fully parallel manner. This has been achieved by replacing the breadth- first search procedure with a parallel method. These algorithms have been compared by testing them on a database of optical coherence tomography images. The comparison of results shows that the proposed implementation of the Canny method on GPU using the CUDA platform improves the speed of execution by 2-100× compared to the central processing unit-based implementation using the OpenCV and MATLAB platforms.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB

KAUST Repository

Klingbeil, G.

2011-02-25

Motivation: The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. Results: The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user\\'s models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. © The Author 2011. Published by Oxford University Press. All rights reserved.

An Accelerator Control Middle Layer Using MATLAB

International Nuclear Information System (INIS)

Portmann, Gregory J.; Corbett, Jeff; Terebilo, Andrei

2005-01-01

Matlab is a matrix manipulation language originally developed to be a convenient language for using the LINPACK and EISPACK libraries. What makes Matlab so appealing for accelerator physics is the combination of a matrix oriented programming language, an active workspace for system variables, powerful graphics capability, built-in math libraries, and platform independence. A number of software toolboxes for accelerators have been written in Matlab--the Accelerator Toolbox (AT) for machine simulations, LOCO for accelerator calibration, Matlab Channel Access Toolbox (MCA) for EPICS connections, and the Middle Layer. This paper will describe the ''middle layer'' software toolbox that resides between the high-level control applications and the low-level accelerator control system. This software was a collaborative effort between ALS (LBNL) and SPEAR3 (SSRL) but easily ports to other machines. Five accelerators presently use this software. The high-level Middle Layer functionality includes energy ramp, configuration control (save/restore), global orbit correction, local photon beam steering, insertion device compensation, beam-based alignment, tune correction, response matrix measurement, and script-based programs for machine physics studies

A new algorithm for 3D reconstruction from support functions

DEFF Research Database (Denmark)

Gardner, Richard; Kiderlen, Markus

2009-01-01

We introduce a new algorithm for reconstructing an unknown shape from a finite number of noisy measurements of its support function. The algorithm, based on a least squares procedure, is very easy to program in standard software such as Matlab and allows, for the first time, good 3D reconstructio...

SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

Science.gov (United States)

Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

2013-01-01

We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.

Kinematic simulation and analysis of robot based on MATLAB

Science.gov (United States)

Liao, Shuhua; Li, Jiong

2018-03-01

The history of industrial automation is characterized by quick update technology, however, without a doubt, the industrial robot is a kind of special equipment. With the help of MATLAB matrix and drawing capacity in the MATLAB environment each link coordinate system set up by using the d-h parameters method and equation of motion of the structure. Robotics, Toolbox programming Toolbox and GUIDE to the joint application is the analysis of inverse kinematics and path planning and simulation, preliminary solve the problem of college students the car mechanical arm positioning theory, so as to achieve the aim of reservation.

Robotics, vision and control fundamental algorithms in Matlab

CERN Document Server

Corke, Peter

2017-01-01

Robotic vision, the combination of robotics and computer vision, involves the application of computer algorithms to data acquired from sensors. The research community has developed a large body of such algorithms but for a newcomer to the field this can be quite daunting. For over 20 years the author has maintained two open-source MATLAB® Toolboxes, one for robotics and one for vision. They provide implementations of many important algorithms and allow users to work with real problems, not just trivial examples. This book makes the fundamental algorithms of robotics, vision and control accessible to all. It weaves together theory, algorithms and examples in a narrative that covers robotics and computer vision separately and together. Using the latest versions of the Toolboxes the author shows how complex problems can be decomposed and solved using just a few simple lines of code. The topics covered are guided by real problems observed by the author over many years as a practitioner of both robotics and compu...

Matlab laser toolbox

NARCIS (Netherlands)

Römer, Gerardus Richardus, Bernardus, Engelina; Huis in 't Veld, Bert; Schmidt, M.; Vollertsen, F.; Geiger, M.

2010-01-01

Matlab® is a program for numeric computation, simulation and visualization, developed by The Mathworks, Inc. It is used heavily in education, research, and industry, for solving general, as well as application area-specific problems, that arise in various disciplines. For this purpose Matlab has

R and Matlab

CERN Document Server

Hiebeler, David E

2015-01-01

The First Book to Explain How a User of R or MATLAB Can Benefit from the OtherIn today's increasingly interdisciplinary world, R and MATLAB® users from different backgrounds must often work together and share code. R and MATLAB® is designed for users who already know R or MATLAB and now need to learn the other platform. The book makes the transition from one platform to the other as quick and painless as possible.Enables R and MATLAB Users to Easily Collaborate and Share CodeThe author covers essential tasks, such as working with matrices and vectors, writing functions and other programming co

A method of measuring and correcting tilt of anti - vibration wind turbines based on screening algorithm

Science.gov (United States)

Xiao, Zhongxiu

2018-04-01

A Method of Measuring and Correcting Tilt of Anti - vibration Wind Turbines Based on Screening Algorithm is proposed in this paper. First of all, we design a device which the core is the acceleration sensor ADXL203, the inclination is measured by installing it on the tower of the wind turbine as well as the engine room. Next using the Kalman filter algorithm to filter effectively by establishing a state space model for signal and noise. Then we use matlab for simulation. Considering the impact of the tower and nacelle vibration on the collected data, the original data and the filtering data are classified and stored by the Screening algorithm, then filter the filtering data to make the output data more accurate. Finally, we eliminate installation errors by using algorithm to achieve the tilt correction. The device based on this method has high precision, low cost and anti-vibration advantages. It has a wide range of application and promotion value.

MatLab Script and Functional Programming

Science.gov (United States)

Shaykhian, Gholam Ali

2007-01-01

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

Science.gov (United States)

Courtney, Jane; Woods, Elena; Scholz, Dimitri; Hall, William W; Gautier, Virginie W

2015-01-01

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation. In addition, MATtrack features a simple user interface, which enables monitoring of Fluorescent Signal Intensity in multiple Regions of Interest, over time. The latter encapsulates a region growing method to automatically delineate the contours of Regions of Interest selected by the user, and performs background and regional Average Fluorescence Tracking, and automatic plotting. Finally, MATtrack computes convenient visualization and exploration tools including a migration map, which provides an overview of the protein intracellular trajectories and accumulation areas. In conclusion, MATtrack is an open source MATLAB-based software package tailored to facilitate the analysis and visualization of large data files derived from real-time live cell fluorescent microscopy using photoconvertible proteins. It is flexible, user friendly, compatible with Windows, Mac, and Linux, and a wide range of data acquisition software. MATtrack is freely available for download at eleceng.dit.ie/courtney/MATtrack.zip.

An enhanced DWBA algorithm in hybrid WDM/TDM EPON networks with heterogeneous propagation delays

Science.gov (United States)

Li, Chengjun; Guo, Wei; Jin, Yaohui; Sun, Weiqiang; Hu, Weisheng

2011-12-01

An enhanced dynamic wavelength and bandwidth allocation (DWBA) algorithm in hybrid WDM/TDM PON is proposed and experimentally demonstrated. In addition to the fairness of bandwidth allocation, this algorithm also considers the varying propagation delays between ONUs and OLT. The simulation based on MATLAB indicates that the improved algorithm has a better performance compared with some other algorithms.

Programming for computations MATLAB/Octave : a gentle introduction to numerical simulations with MATLAB/Octave

CERN Document Server

Linge, Svein

2016-01-01

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

A platform for dynamic simulation and control of movement based on OpenSim and MATLAB.

Science.gov (United States)

Mansouri, Misagh; Reinbolt, Jeffrey A

2012-05-11

Numerical simulations play an important role in solving complex engineering problems and have the potential to revolutionize medical decision making and treatment strategies. In this paper, we combine the rapid model-based design, control systems and powerful numerical method strengths of MATLAB/Simulink with the simulation and human movement dynamics strengths of OpenSim by developing a new interface between the two software tools. OpenSim is integrated with Simulink using the MATLAB S-function mechanism, and the interface is demonstrated using both open-loop and closed-loop control systems. While the open-loop system uses MATLAB/Simulink to separately reproduce the OpenSim Forward Dynamics Tool, the closed-loop system adds the unique feature of feedback control to OpenSim, which is necessary for most human movement simulations. An arm model example was successfully used in both open-loop and closed-loop cases. For the open-loop case, the simulation reproduced results from the OpenSim Forward Dynamics Tool with root mean square (RMS) differences of 0.03° for the shoulder elevation angle and 0.06° for the elbow flexion angle. MATLAB's variable step-size integrator reduced the time required to generate the forward dynamic simulation from 7.1s (OpenSim) to 2.9s (MATLAB). For the closed-loop case, a proportional-integral-derivative controller was used to successfully balance a pole on model's hand despite random force disturbances on the pole. The new interface presented here not only integrates the OpenSim and MATLAB/Simulink software tools, but also will allow neuroscientists, physiologists, biomechanists, and physical therapists to adapt and generate new solutions as treatments for musculoskeletal conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks.

Science.gov (United States)

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-06-26

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

Comparative performance analysis of the artificial-intelligence-based thermal control algorithms for the double-skin building

International Nuclear Information System (INIS)

Moon, Jin Woo

2015-01-01

This study aimed at developing artificial-intelligence-(AI)-theory-based optimal control algorithms for improving the indoor temperature conditions and heating energy efficiency of the double-skin buildings. For this, one conventional rule-based and four AI-based algorithms were developed, including artificial neural network (ANN), fuzzy logic (FL), and adaptive neuro fuzzy inference systems (ANFIS), for operating the surface openings of the double skin and the heating system. A numerical computer simulation method incorporating the matrix laboratory (MATLAB) and the transient systems simulation (TRNSYS) software was used for the comparative performance tests. The analysis results revealed that advanced thermal-environment comfort and stability can be provided by the AI-based algorithms. In particular, the FL and ANFIS algorithms were superior to the ANN algorithm in terms of providing better thermal conditions. The ANN-based algorithm, however, proved its potential to be the most energy-efficient and stable strategy among the four AI-based algorithms. It can be concluded that the optimal algorithm can be differently determined according to the major focus of the strategy. If comfortable thermal condition is the principal interest, then the FL or ANFIS algorithm could be the proper solution, and if energy saving for space heating and system operation stability is the main concerns, then the ANN-based algorithm may be applicable. - Highlights: • Integrated control algorithms were developed for the heating system and surface openings. • AI theories were applied to the control algorithms. • ANN, FL, and ANFIS were the applied AI theories. • Comparative performance tests were conducted using computer simulation. • AI algorithms presented superior temperature environment.

The Research of Histogram Enhancement Technique Based on Matlab Software

Directory of Open Access Journals (Sweden)

Li Kai

2014-08-01

Full Text Available Histogram enhancement technique has been widely applied as a typical pattern in digital image processing. The paper is based on Matlab software, through the two ways of histogram equalization and histogram specification technologies to deal with the darker images, using two methods of partial equilibrium and mapping histogram to transform the original histograms, thereby enhanced the image information. The results show that these two kinds of techniques both can significantly improve the image quality and enhance the image feature.

MultiElec: A MATLAB Based Application for MEA Data Analysis.

Science.gov (United States)

Georgiadis, Vassilis; Stephanou, Anastasis; Townsend, Paul A; Jackson, Thomas R

2015-01-01

We present MultiElec, an open source MATLAB based application for data analysis of microelectrode array (MEA) recordings. MultiElec displays an extremely user-friendly graphic user interface (GUI) that allows the simultaneous display and analysis of voltage traces for 60 electrodes and includes functions for activation-time determination, the production of activation-time heat maps with activation time and isoline display. Furthermore, local conduction velocities are semi-automatically calculated along with their corresponding vector plots. MultiElec allows ad hoc signal suppression, enabling the user to easily and efficiently handle signal artefacts and for incomplete data sets to be analysed. Voltage traces and heat maps can be simply exported for figure production and presentation. In addition, our platform is able to produce 3D videos of signal progression over all 60 electrodes. Functions are controlled entirely by a single GUI with no need for command line input or any understanding of MATLAB code. MultiElec is open source under the terms of the GNU General Public License as published by the Free Software Foundation, version 3. Both the program and source code are available to download from http://www.cancer.manchester.ac.uk/MultiElec/.

MOCCASIN: converting MATLAB ODE models to SBML.

Science.gov (United States)

Gómez, Harold F; Hucka, Michael; Keating, Sarah M; Nudelman, German; Iber, Dagmar; Sealfon, Stuart C

2016-06-15

MATLAB is popular in biological research for creating and simulating models that use ordinary differential equations (ODEs). However, sharing or using these models outside of MATLAB is often problematic. A community standard such as Systems Biology Markup Language (SBML) can serve as a neutral exchange format, but translating models from MATLAB to SBML can be challenging-especially for legacy models not written with translation in mind. We developed MOCCASIN (Model ODE Converter for Creating Automated SBML INteroperability) to help. MOCCASIN can convert ODE-based MATLAB models of biochemical reaction networks into the SBML format. MOCCASIN is available under the terms of the LGPL 2.1 license (http://www.gnu.org/licenses/lgpl-2.1.html). Source code, binaries and test cases can be freely obtained from https://github.com/sbmlteam/moccasin : mhucka@caltech.edu More information is available at https://github.com/sbmlteam/moccasin. © The Author 2016. Published by Oxford University Press.

Performance evaluation for volumetric segmentation of multiple sclerosis lesions using MATLAB and computing engine in the graphical processing unit (GPU)

Science.gov (United States)

Le, Anh H.; Park, Young W.; Ma, Kevin; Jacobs, Colin; Liu, Brent J.

2010-03-01

Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.

Some selected quantitative methods of thermal image analysis in Matlab.

Science.gov (United States)

Koprowski, Robert

2016-05-01

The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

KiT: a MATLAB package for kinetochore tracking.

Science.gov (United States)

Armond, Jonathan W; Vladimirou, Elina; McAinsh, Andrew D; Burroughs, Nigel J

2016-06-15

During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. Supplementary data are available at Bioinformatics online. jonathan.armond@warwick.ac.uk. © The Author 2016. Published by Oxford University Press.

New technique for global solar radiation forecasting by simulated annealing and genetic algorithms using

International Nuclear Information System (INIS)

Tolabi, H.B.; Ayob, S.M.

2014-01-01

In this paper, a novel approach based on simulated annealing algorithm as a meta-heuristic method is implemented in MATLAB software to estimate the monthly average daily global solar radiation on a horizontal surface for six different climate cities of Iran. A search method based on genetic algorithm is applied to accelerate problem solving. Results show that simulated annealing based on genetic algorithm search is a suitable method to find the global solar radiation. (author)

MATLAB-based program for optimization of quantum cascade laser active region parameters and calculation of output characteristics in magnetic field

Science.gov (United States)

Smiljanić, J.; Žeželj, M.; Milanović, V.; Radovanović, J.; Stanković, I.

2014-03-01

A strong magnetic field applied along the growth direction of a quantum cascade laser (QCL) active region gives rise to a spectrum of discrete energy states, the Landau levels. By combining quantum engineering of a QCL with a static magnetic field, we can selectively inhibit/enhance non-radiative electron relaxation process between the relevant Landau levels of a triple quantum well and realize a tunable surface emitting device. An efficient numerical algorithm implementation is presented of optimization of GaAs/AlGaAs QCL region parameters and calculation of output properties in the magnetic field. Both theoretical analysis and MATLAB implementation are given for LO-phonon and interface roughness scattering mechanisms on the operation of QCL. At elevated temperatures, electrons in the relevant laser states absorb/emit more LO-phonons which results in reduction of the optical gain. The decrease in the optical gain is moderated by the occurrence of interface roughness scattering, which remains unchanged with increasing temperature. Using the calculated scattering rates as input data, rate equations can be solved and population inversion and the optical gain obtained. Incorporation of the interface roughness scattering mechanism into the model did not create new resonant peaks of the optical gain. However, it resulted in shifting the existing peaks positions and overall reduction of the optical gain. Catalogue identifier: AERL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERL_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 37763 No. of bytes in distributed program, including test data, etc.: 2757956 Distribution format: tar.gz Programming language: MATLAB. Computer: Any capable of running MATLAB version R2010a or higher. Operating system: Any platform

A MATLAB companion for multivariable calculus

CERN Document Server

Cooper, Jeffery

2001-01-01

Offering a concise collection of MatLab programs and exercises to accompany a third semester course in multivariable calculus, A MatLab Companion for Multivariable Calculus introduces simple numerical procedures such as numerical differentiation, numerical integration and Newton''s method in several variables, thereby allowing students to tackle realistic problems. The many examples show students how to use MatLab effectively and easily in many contexts. Numerous exercises in mathematics and applications areas are presented, graded from routine to more demanding projects requiring some programming. Matlab M-files are provided on the Harcourt/Academic Press web site at http://www.harcourt-ap.com/matlab.html.* Computer-oriented material that complements the essential topics in multivariable calculus* Main ideas presented with examples of computations and graphics displays using MATLAB * Numerous examples of short code in the text, which can be modified for use with the exercises* MATLAB files are used to implem...

Parallelizing AT with MatlabMPI

International Nuclear Information System (INIS)

2011-01-01

The Accelerator Toolbox (AT) is a high-level collection of tools and scripts specifically oriented toward solving problems dealing with computational accelerator physics. It is integrated into the MATLAB environment, which provides an accessible, intuitive interface for accelerator physicists, allowing researchers to focus the majority of their efforts on simulations and calculations, rather than programming and debugging difficulties. Efforts toward parallelization of AT have been put in place to upgrade its performance to modern standards of computing. We utilized the packages MatlabMPI and pMatlab, which were developed by MIT Lincoln Laboratory, to set up a message-passing environment that could be called within MATLAB, which set up the necessary pre-requisites for multithread processing capabilities. On local quad-core CPUs, we were able to demonstrate processor efficiencies of roughly 95% and speed increases of nearly 380%. By exploiting the efficacy of modern-day parallel computing, we were able to demonstrate incredibly efficient speed increments per processor in AT's beam-tracking functions. Extrapolating from prediction, we can expect to reduce week-long computation runtimes to less than 15 minutes. This is a huge performance improvement and has enormous implications for the future computing power of the accelerator physics group at SSRL. However, one of the downfalls of parringpass is its current lack of transparency; the pMatlab and MatlabMPI packages must first be well-understood by the user before the system can be configured to run the scripts. In addition, the instantiation of argument parameters requires internal modification of the source code. Thus, parringpass, cannot be directly run from the MATLAB command line, which detracts from its flexibility and user-friendliness. Future work in AT's parallelization will focus on development of external functions and scripts that can be called from within MATLAB and configured on multiple nodes, while

Modeling of diatomic molecule using the Morse potential and the Verlet algorithm

Energy Technology Data Exchange (ETDEWEB)

Fidiani, Elok [Department of Physics, Parahyangan Catholic University, Bandung-Jawa Barat (Indonesia)

2016-03-11

Performing molecular modeling usually uses special software for Molecular Dynamics (MD) such as: GROMACS, NAMD, JMOL etc. Molecular dynamics is a computational method to calculate the time dependent behavior of a molecular system. In this work, MATLAB was used as numerical method for a simple modeling of some diatomic molecules: HCl, H{sub 2} and O{sub 2}. MATLAB is a matrix based numerical software, in order to do numerical analysis, all the functions and equations describing properties of atoms and molecules must be developed manually in MATLAB. In this work, a Morse potential was generated to describe the bond interaction between the two atoms. In order to analyze the simultaneous motion of molecules, the Verlet Algorithm derived from Newton’s Equations of Motion (classical mechanics) was operated. Both the Morse potential and the Verlet algorithm were integrated using MATLAB to derive physical properties and the trajectory of the molecules. The data computed by MATLAB is always in the form of a matrix. To visualize it, Visualized Molecular Dynamics (VMD) was performed. Such method is useful for development and testing some types of interaction on a molecular scale. Besides, this can be very helpful for describing some basic principles of molecular interaction for educational purposes.

Modeling of diatomic molecule using the Morse potential and the Verlet algorithm

International Nuclear Information System (INIS)

Fidiani, Elok

2016-01-01

Performing molecular modeling usually uses special software for Molecular Dynamics (MD) such as: GROMACS, NAMD, JMOL etc. Molecular dynamics is a computational method to calculate the time dependent behavior of a molecular system. In this work, MATLAB was used as numerical method for a simple modeling of some diatomic molecules: HCl, H_2 and O_2. MATLAB is a matrix based numerical software, in order to do numerical analysis, all the functions and equations describing properties of atoms and molecules must be developed manually in MATLAB. In this work, a Morse potential was generated to describe the bond interaction between the two atoms. In order to analyze the simultaneous motion of molecules, the Verlet Algorithm derived from Newton’s Equations of Motion (classical mechanics) was operated. Both the Morse potential and the Verlet algorithm were integrated using MATLAB to derive physical properties and the trajectory of the molecules. The data computed by MATLAB is always in the form of a matrix. To visualize it, Visualized Molecular Dynamics (VMD) was performed. Such method is useful for development and testing some types of interaction on a molecular scale. Besides, this can be very helpful for describing some basic principles of molecular interaction for educational purposes.

DESIGNING APPLICATION OF ANT COLONY SYSTEM ALGORITHM FOR THE SHORTEST ROUTE OF BANDA ACEH CITY AND ACEH BESAR REGENCY TOURISM BY USING GRAPHICAL USER INTERFACE MATLAB

Directory of Open Access Journals (Sweden)

Durisman Durisman

2017-09-01

Full Text Available Banda Aceh city and Aceh Besar Regency are two of the leading tourism areas located in the province of Aceh. For travelling, there are some important things to be considered, such as determining schedule and distance of tourism. Every tourist certainly chooses the shortest route to reach the destination since it can save time, energy, and money. The purpose of this reserach is to develop a method that can be used in calculating the shortest route and applied to the tourism of Banda Aceh city and Aceh Besar regency. In this reserach, Ant Colony Optimization algorithm is used to determine the shortest route to tourism of Banda Aceh city and Aceh Besar regency. From the analysis made by using both manual calculation and  GUI MATLAB program application test, the shortest route can be obtained with a minimum distance of 120.85 km in one travel. Based on the test result, the application for tourism (in Banda Aceh city and Aceh Besar regency shortest route searching built by utilizing the Ant Colony Optimization algorithm can find optimal route.  Keyword: tourism, the shortest route, Ant Colony Optimization

Numerical linear algebra a concise introduction with Matlab and Julia

CERN Document Server

Bornemann, Folkmar

2018-01-01

This book offers an introduction to the algorithmic-numerical thinking using basic problems of linear algebra. By focusing on linear algebra, it ensures a stronger thematic coherence than is otherwise found in introductory lectures on numerics. The book highlights the usefulness of matrix partitioning compared to a component view, leading not only to a clearer notation and shorter algorithms, but also to significant runtime gains in modern computer architectures. The algorithms and accompanying numerical examples are given in the programming environment MATLAB, and additionally – in an appendix – in the future-oriented, freely accessible programming language Julia. This book is suitable for a two-hour lecture on numerical linear algebra from the second semester of a bachelor's degree in mathematics.

Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax Timing-based location estimation for OFDM signals with applications in LTE, WLAN and Wimax

OpenAIRE

Juárez Leria, Víctor

2012-01-01

Projecte realitzat en el marc d'un programa de mobilitat amb la Tampere University of Technology (Tampereen Teknillinen Yliopisto) [ANGLÈS] Literature study of various preamble-based and non-preamble-based timing synchronization algorithms in OFDM - Implementation (in Matlab) of the following preamble-based algorithms: Schmidl, Minn, Park, Kim, Ren and Kang. Implementation (in Matlab) of Correlation-Based Timing Synchronization and MUltiple SIgnal Classification estimators. Comparison of v...

Visual media processing using Matlab beginner's guide

CERN Document Server

Siogkas, George

2013-01-01

Written in a friendly, Beginner's Guide format, showing the user how to use the digital media aspects of Matlab (image, video, sound) in a practical, tutorial-based style.This is great for novice programmers in any language who would like to use Matlab as a tool for their image and video processing needs, and also comes in handy for photographers or video editors with even less programming experience wanting to find an all-in-one tool for their tasks.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Directory of Open Access Journals (Sweden)

Sandeep Pirbhulal

2015-06-01

Full Text Available Body Sensor Network (BSN is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG, Photoplethysmography (PPG, Electrocardiogram (ECG, etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA, Data Encryption Standard (DES and Rivest Shamir Adleman (RSA. Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Science.gov (United States)

Pirbhulal, Sandeep; Zhang, Heye; Mukhopadhyay, Subhas Chandra; Li, Chunyue; Wang, Yumei; Li, Guanglin; Wu, Wanqing; Zhang, Yuan-Ting

2015-01-01

Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption. PMID:26131666

Control of baker’s yeast fermentation : PID and fuzzy algorithms

OpenAIRE

Machado, Carlos; Gomes, Pedro; Soares, Rui; Pereira, Silvia; Soares, Filomena

2001-01-01

A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the non-linear process.

Faults Detection in a Photovoltaic Generator by Using Matlab Simulink and the chipKIT Max32 Board

Directory of Open Access Journals (Sweden)

Riadh Khenfer

2014-01-01

Full Text Available This paper presents a laboratory with equipment and an algorithm for teaching graduate students the monitoring and the diagnosis of PV arrays. The contribution is the presentation of an algorithm to detect and localize the fault, in photovoltaic generator when a limited number of voltage sensors are used. An I-V curve tracer using a capacitive load is exploited to measure the I-V characteristics of PV arrays. Such measurement allows characterization of PV arrays on-site, under real operating conditions, and provides also information for the detection of potential array anomalies. This I-V curve tracer is based on a microcontroller board family called chipKIT Max32 which is a popular platform for physical computing. A user program can be developed visually on a PC side via the graphical user interface (GUI in Matlab Simulink, where the chipKIT Max32 of Digilent which is a low-cost board is designed for use with the Arduinompid software. The obtained results from the partial shade default showed the effectiveness of the proposed diagnosis method and the good functioning of this board with the Matlab/Simulink environment.

Comprehensive asynchronous symmetric rendezvous algorithm in ...

Indian Academy of Sciences (India)

Meenu Chawla

2017-11-10

Nov 10, 2017 ... Simulation results affirm that CASR algorithm performs better in terms of average time-to-rendezvous as compared ... process; neighbour discovery; symmetric rendezvous algorithm. 1. .... dezvous in finite time under the symmetric model. The CH ..... CASR algorithm in Matlab 7.11 and performed several.

Chaotic Image Scrambling Algorithm Based on S-DES

International Nuclear Information System (INIS)

Yu, X Y; Zhang, J; Ren, H E; Xu, G S; Luo, X Y

2006-01-01

With the security requirement improvement of the image on the network, some typical image encryption methods can't meet the demands of encryption, such as Arnold cat map and Hilbert transformation. S-DES system can encrypt the input binary flow of image, but the fixed system structure and few keys will still bring some risks. However, the sensitivity of initial value that Logistic chaotic map can be well applied to the system of S-DES, which makes S-DES have larger random and key quantities. A dual image encryption algorithm based on S-DES and Logistic map is proposed. Through Matlab simulation experiments, the key quantities will attain 10 17 and the encryption speed of one image doesn't exceed one second. Compared to traditional methods, it has some merits such as easy to understand, rapid encryption speed, large keys and sensitivity to initial value

Three-dimensional rendering of segmented object using matlab - biomed 2010.

Science.gov (United States)

Anderson, Jeffrey R; Barrett, Steven F

2010-01-01

The three-dimensional rendering of microscopic objects is a difficult and challenging task that often requires specialized image processing techniques. Previous work has been described of a semi-automatic segmentation process of fluorescently stained neurons collected as a sequence of slice images with a confocal laser scanning microscope. Once properly segmented, each individual object can be rendered and studied as a three-dimensional virtual object. This paper describes the work associated with the design and development of Matlab files to create three-dimensional images from the segmented object data previously mentioned. Part of the motivation for this work is to integrate both the segmentation and rendering processes into one software application, providing a seamless transition from the segmentation tasks to the rendering and visualization tasks. Previously these tasks were accomplished on two different computer systems, windows and Linux. This transition basically limits the usefulness of the segmentation and rendering applications to those who have both computer systems readily available. The focus of this work is to create custom Matlab image processing algorithms for object rendering and visualization, and merge these capabilities to the Matlab files that were developed especially for the image segmentation task. The completed Matlab application will contain both the segmentation and rendering processes in a single graphical user interface, or GUI. This process for rendering three-dimensional images in Matlab requires that a sequence of two-dimensional binary images, representing a cross-sectional slice of the object, be reassembled in a 3D space, and covered with a surface. Additional segmented objects can be rendered in the same 3D space. The surface properties of each object can be varied by the user to aid in the study and analysis of the objects. This inter-active process becomes a powerful visual tool to study and understand microscopic objects.

Simulaser, a graphical laser simulator based on Matlab Simulink

CSIR Research Space (South Africa)

Jacobs, Cobus

2016-07-01

Full Text Available We present a single-element plane-wave laser rate equation model and its implementation as a graphical laser simulation library using Matlab Simulink. Simulink’s graphical interface and vector capabilities provide a unique layer of abstraction...

Improve Data Mining and Knowledge Discovery through the use of MatLab

Science.gov (United States)

Shaykahian, Gholan Ali; Martin, Dawn Elliott; Beil, Robert

2011-01-01

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(TradeMark)(MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and

ADAMS-MATLAB Co-Simulation of A Serial Manipulator

Directory of Open Access Journals (Sweden)

Parthasarathy Tejaswin

2017-01-01

Full Text Available This paper presents the dynamic modelling and simulation of a now redundant robot, Mitsubishi RM-501, and proposes a general algorithm for experimental simulation in kinematics, dynamics and control analysis to any such robot. Through reverse engineering, a model as accurate as the real robot was developed in SolidWorks.The simulations of the same were performed in ADAMS (dynamicmodeling software offered by MSC Software Corpalong with MATLAB for motion studies and control dynamics. Finally, with a user-input path the accuracy and precision of the simulator was verified.

Matlab enhanced multi-threaded tomography optimization sequence (MEMTOS)

International Nuclear Information System (INIS)

Lum, Edward S.; Pope, Chad L.

2016-01-01

Highlights: • Monte Carlo simulation of spent nuclear fuel assembly neutron computed tomography. • Optimized parallel calculations conducted from within the MATLAB environment. • Projection difference technique used to identify anomalies in spent nuclear fuel assemblies. - Abstract: One challenge associated with spent nuclear fuel assemblies is the lack of non-destructive analysis techniques to determine if fuel pins have been removed or replaced or if there are significant defects associated with fuel pins deep within a fuel assembly. Neutron computed tomography is a promising technique for addressing these qualitative issues. Monte Carlo simulation of spent nuclear fuel neutron computed tomography allows inexpensive process investigation and optimization. The main purpose of this work is to provide a fully automated advanced simulation framework for the analysis of spent nuclear fuel inspection using neutron computed tomography. The simulation framework, called Matlab Enhanced Multi-Threaded Tomography Optimization Sequence (MEMTOS) not only automates the simulation process, but also generates superior tomography image results. MEMTOS is written in the MATLAB scripting language and addresses file management, parallel Monte Carlo execution, results extraction, and tomography image generation. This paper describes the mathematical basis for neutron computed tomography, the Monte Carlo technique used to simulate neutron computed tomography, and the overall tomography simulation optimization algorithm. Sequence results presented include overall simulation speed enhancement, tomography and image results obtained for Experimental Breeder Reactor II spent fuel assemblies and light water reactor fuel assemblies. Optimization using a projection difference technique are also described.

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

Science.gov (United States)

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

Essential Matlab and Octave

CERN Document Server

Rogel-Salazar, Jesus

2014-01-01

""This is an excellent book for anyone approaching MATLAB or Octave for the first time. The pleasant language used throughout creates the sensation of having the author by your side. … An interesting feature are the examples used to explain the use of functions and operations. … compared to similar texts on Octave and MATLAB, the author introduces at an early stage how to produce line and surface plots with MATLAB and Octave. It is very attractive to students to be able to quickly produce plots with scientific journal quality. … The margin notes are great as they can also work as virtual bookm

MATLAB 3A

DEFF Research Database (Denmark)

Freil, Ole; Kristiansen, Heidi; Kaas, Thomas

MATLAB 3a – Matematiklaboratoriet er en elevbog til første halvdel af 3. klasse. Bogen indeholder fire kapitler: 'Store tal og regnemåder', 'Kan du tegne det?', 'Gange og division', 'Undersøg data og chance'.......MATLAB 3a – Matematiklaboratoriet er en elevbog til første halvdel af 3. klasse. Bogen indeholder fire kapitler: 'Store tal og regnemåder', 'Kan du tegne det?', 'Gange og division', 'Undersøg data og chance'....

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

Science.gov (United States)

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

Digital speech processing using Matlab

CERN Document Server

Gopi, E S

2014-01-01

Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

Solving applied mathematical problems with Matlab

CERN Document Server

Xue, Dingyu

2008-01-01

Computer Mathematics Language-An Overview. Fundamentals of MATLAB Programming. Calculus Problems. MATLAB Computations of Linear Algebra Problems. Integral Transforms and Complex Variable Functions. Solutions to Nonlinear Equations and Optimization Problems. MATLAB Solutions to Differential Equation Problems. Solving Interpolations and Approximations Problems. Solving Probability and Mathematical Statistics Problems. Nontraditional Solution Methods for Mathematical Problems.

Kinematic analysis of the finger exoskeleton using MATLAB/Simulink.

Science.gov (United States)

Nasiłowski, Krzysztof; Awrejcewicz, Jan; Lewandowski, Donat

2014-01-01

A paralyzed and not fully functional part of human body can be supported by the properly designed exoskeleton system with motoric abilities. It can help in rehabilitation, or movement of a disabled/paralyzed limb. Both suitably selected geometry and specialized software are studied applying the MATLAB environment. A finger exoskeleton was the base for MATLAB/Simulink model. Specialized software, such as MATLAB/Simulink give us an opportunity to optimize calculation reaching precise results, which help in next steps of design process. The calculations carried out yield information regarding movement relation between three functionally connected actuators and showed distance and velocity changes during the whole simulation time.

Channel Access Client Toolbox for Matlab

International Nuclear Information System (INIS)

2002-01-01

This paper reports on MATLAB Channel Access (MCA) Toolbox--MATLAB [1] interface to EPICS Channel Access (CA) client library. We are developing the toolbox for SPEAR3 accelerator controls, but it is of general use for accelerator and experimental physics applications programming. It is packaged as a MATLAB toolbox to allow easy development of complex CA client applications entirely in MATLAB. The benefits include: the ability to calculate and display parameters that use EPICS process variables as inputs, availability of MATLAB graphics tools for user interface design, and integration with the MATLABbased accelerator modeling software - Accelerator Toolbox [2-4]. Another purpose of this paper is to propose a feasible path to a synergy between accelerator control systems and accelerator simulation codes, the idea known as on-line accelerator model

Open Source Power Plant Simulator Development Under Matlab Environment

International Nuclear Information System (INIS)

Ratemi, W.M.; Fadilah, S.M.; Abonoor, N

2008-01-01

In this paper an open source programming approach is targeted for the development of power plant simulator under Matlab environment. With this approach many individuals can contribute to the development of the simulator by developing different orders of complexities of the power plant components. Such modules can be modeled based on physical principles, or using neural networks or other methods. All of these modules are categorized in Matlab library, of which the user can select and build up his simulator. Many international companies developed its own authoring tool for the development of its simulators, and hence it became its own property available for high costs. Matlab is a general software developed by mathworks that can be used with its toolkits as the authoring tool for the development of components by different individuals, and through the appropriate coordination, different plant simulators, nuclear, traditional , or even research reactors can be computerly assembled. In this paper, power plant components such as a pressurizer, a reactor, a steam generator, a turbine, a condenser, a feedwater heater, a valve, a pump are modeled based on physical principles. Also a prototype modeling of a reactor ( a scram case) based on neural networks is developed. These modules are inserted in two different Matlab libraries one called physical and the other is called neural. Furthermore, during the simulation one can pause and shuffle the modules selected from the two libraries and then proceed the simulation. Also, under the Matlab environment a PID controller is developed for multi-loop plant which can be integrated for the control of the appropriate developed simulator. This paper is an attempt to base the open source approach for the development of power plant simulators or even research reactor simulators. It then requires the coordination among interested individuals or institutions to set it to professionalism. (author)

RenderToolbox3: MATLAB tools that facilitate physically based stimulus rendering for vision research.

Science.gov (United States)

Heasly, Benjamin S; Cottaris, Nicolas P; Lichtman, Daniel P; Xiao, Bei; Brainard, David H

2014-02-07

RenderToolbox3 provides MATLAB utilities and prescribes a workflow that should be useful to researchers who want to employ graphics in the study of vision and perhaps in other endeavors as well. In particular, RenderToolbox3 facilitates rendering scene families in which various scene attributes and renderer behaviors are manipulated parametrically, enables spectral specification of object reflectance and illuminant spectra, enables the use of physically based material specifications, helps validate renderer output, and converts renderer output to physical units of radiance. This paper describes the design and functionality of the toolbox and discusses several examples that demonstrate its use. We have designed RenderToolbox3 to be portable across computer hardware and operating systems and to be free and open source (except for MATLAB itself). RenderToolbox3 is available at https://github.com/DavidBrainard/RenderToolbox3.

Configuration and debug of field programmable gate arrays using MATLAB[reg)/SIMULINK[reg

International Nuclear Information System (INIS)

Grout, I; Ryan, J; O'Shea, T

2005-01-01

Increasingly, the need to seamlessly link high-level behavioural descriptions of electronic hardware for modelling and simulation purposes to the final application hardware highlights the gap between the high-level behavioural descriptions of the required circuit functionality (considering here digital logic) in commonly used mathematical modelling tools, and the hardware description languages such as VHDL and Verilog-HDL. In this paper, the linking of a MATLAB[reg] model for digital algorithm for implementation on a programmable logic device for design synthesis from the MATLAB[reg] model into VHDL is discussed. This VHDL model is itself synthesised and downloaded to the target Field Programmable Gate Array, for normal operation and also for design debug purposes. To demonstrate this, a circuit architecture mapped from a SIMULINK[reg] model is presented. The rationale is for a seamless interface between the initial algorithm development and the target hardware, enabling the hardware to be debugged and compared to the simulated model from a single interface for use with by a non-expert in the programmable logic and hardware description language use

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

Science.gov (United States)

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark; Knowles, David W.; Weber, Gunther H.; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

2011-03-30

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

DACE - A Matlab Kriging Toolbox

DEFF Research Database (Denmark)

2002-01-01

DACE, Design and Analysis of Computer Experiments, is a Matlab toolbox for working with kriging approximations to computer models.......DACE, Design and Analysis of Computer Experiments, is a Matlab toolbox for working with kriging approximations to computer models....

UTV Expansion Pack: Special-Purpose Rank-Revealing Algorithms

DEFF Research Database (Denmark)

Fierro, Ricardo D.; Hansen, Per Christian

2005-01-01

This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-r...... values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval.......This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank......-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which - despite its simplicity - is able to capture all the dominant singular...

Microcontroller USB interfacing with MATLAB GUI for low cost medical ultrasound scanners

Directory of Open Access Journals (Sweden)

Jean Rossario Raj

2016-06-01

Full Text Available This paper presents an 8051 microcontroller-based control of ultrasound scanner prototype hardware from a host laptop MATLAB GUI. The hardware control of many instruments is carried out by microcontrollers. These microcontrollers are in turn controlled from a GUI residing in a computing machine that is connected over the USB interface. Conventionally such GUIs are developed using ‘C’ language or its variants. But MATLAB GUI is a better tool, when such GUI programs need to do huge image/video processing. However interfacing MATLAB with the microcontroller is a challenging task. Here, MATLAB interfacing through an intermediate MEX ‘C’ language program is presented. This paper outlines the MEX programming methods for achieving the smooth interfacing of microcontrollers with MATLAB GUI.

Matpar: Parallel Extensions for MATLAB

Science.gov (United States)

Springer, P. L.

1998-01-01

Matpar is a set of client/server software that allows a MATLAB user to take advantage of a parallel computer for very large problems. The user can replace calls to certain built-in MATLAB functions with calls to Matpar functions.

Introduction à MATLAB

OpenAIRE

Zenou, Emmanuel

2013-01-01

Cette initiation à MatLab a pour objectif de se familiariser à un outil très utilisé par la communauté scientifique dans les laboratoires et dans l'industrie. Il a également pour objectif d'initier (pour ceux qui n'y ont jamais touché) à la programmation et à l'algorithmique, ce qui est indispensable à tout bon ingénieur aujourd'hui. En effet, beaucoup de notions introduites ici ne sont pas propres à MatLab mais à tout langage structuré comme le C/C++, le Java, etc.

Computational mathematics models, methods, and analysis with Matlab and MPI

CERN Document Server

White, Robert E

2004-01-01

Computational Mathematics: Models, Methods, and Analysis with MATLAB and MPI explores and illustrates this process. Each section of the first six chapters is motivated by a specific application. The author applies a model, selects a numerical method, implements computer simulations, and assesses the ensuing results. These chapters include an abundance of MATLAB code. By studying the code instead of using it as a "black box, " you take the first step toward more sophisticated numerical modeling. The last four chapters focus on multiprocessing algorithms implemented using message passing interface (MPI). These chapters include Fortran 9x codes that illustrate the basic MPI subroutines and revisit the applications of the previous chapters from a parallel implementation perspective. All of the codes are available for download from www4.ncsu.edu./~white.This book is not just about math, not just about computing, and not just about applications, but about all three--in other words, computational science. Whether us...

Processing of hyperspectral medical images applications in dermatology using Matlab

CERN Document Server

Koprowski, Robert

2017-01-01

This book presents new methods of analyzing and processing hyperspectral medical images, which can be used in diagnostics, for example for dermatological images. The algorithms proposed are fully automatic and the results obtained are fully reproducible. Their operation was tested on a set of several thousands of hyperspectral images and they were implemented in Matlab. The presented source code can be used without licensing restrictions. This is a valuable resource for computer scientists, bioengineers, doctoral students, and dermatologists interested in contemporary analysis methods.

KALMTOOL for use with MATLAB

DEFF Research Database (Denmark)

Nørgaard, Peter Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

2003-01-01

The KALMTOOL toolbox is a set of MATLAB tools for state estimation for nonlinear systems. The toolbox contains functions for extended Kalman filtering as well as for two new filters called the DD1 filter and the DD2 filter. The toolbox specifically addresses the problem of not having observations...... available at all sampling instants. All functions are available as m-functions but for faster (much faster!) execution, the DD1 and DD2 filters are also available as C Mex files for MATLAB under Windows and Linux. The toolbox requires MATLAB 6. No additional toolboxes are required....

Transportation channels calculation method in MATLAB

International Nuclear Information System (INIS)

Averyanov, G.P.; Budkin, V.A.; Dmitrieva, V.V.; Osadchuk, I.O.; Bashmakov, Yu.A.

2014-01-01

Output devices and charged particles transport channels are necessary components of any modern particle accelerator. They differ both in sizes and in terms of focusing elements depending on particle accelerator type and its destination. A package of transport line designing codes for magnet optical channels in MATLAB environment is presented in this report. Charged particles dynamics in a focusing channel can be studied easily by means of the matrix technique. MATLAB usage is convenient because its information objects are matrixes. MATLAB allows the use the modular principle to build the software package. Program blocks are small in size and easy to use. They can be executed separately or commonly. A set of codes has a user-friendly interface. Transport channel construction consists of focusing lenses (doublets and triplets). The main of the magneto-optical channel parameters are total length and lens position and parameters of the output beam in the phase space (channel acceptance, beam emittance - beam transverse dimensions, particles divergence and image stigmaticity). Choice of the channel operation parameters is based on the conditions for satisfying mutually competing demands. And therefore the channel parameters calculation is carried out by using the search engine optimization techniques.

Optimized design on condensing tubes high-speed TIG welding technology magnetic control based on genetic algorithm

Science.gov (United States)

Lu, Lin; Chang, Yunlong; Li, Yingmin; Lu, Ming

2013-05-01

An orthogonal experiment was conducted by the means of multivariate nonlinear regression equation to adjust the influence of external transverse magnetic field and Ar flow rate on welding quality in the process of welding condenser pipe by high-speed argon tungsten-arc welding (TIG for short). The magnetic induction and flow rate of Ar gas were used as optimum variables, and tensile strength of weld was set to objective function on the base of genetic algorithm theory, and then an optimal design was conducted. According to the request of physical production, the optimum variables were restrained. The genetic algorithm in the MATLAB was used for computing. A comparison between optimum results and experiment parameters was made. The results showed that the optimum technologic parameters could be chosen by the means of genetic algorithm with the conditions of excessive optimum variables in the process of high-speed welding. And optimum technologic parameters of welding coincided with experiment results.

Flexible job-shop scheduling based on genetic algorithm and simulation validation

Directory of Open Access Journals (Sweden)

Zhou Erming

2017-01-01

Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.

MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

Science.gov (United States)

Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

Advanced Dynamics Analytical and Numerical Calculations with MATLAB

CERN Document Server

Marghitu, Dan B

2012-01-01

Advanced Dynamics: Analytical and Numerical Calculations with MATLAB provides a thorough, rigorous presentation of kinematics and dynamics while using MATLAB as an integrated tool to solve problems. Topics presented are explained thoroughly and directly, allowing fundamental principles to emerge through applications from areas such as multibody systems, robotics, spacecraft and design of complex mechanical devices. This book differs from others in that it uses symbolic MATLAB for both theory and applications. Special attention is given to solutions that are solved analytically and numerically using MATLAB. The illustrations and figures generated with MATLAB reinforce visual learning while an abundance of examples offer additional support. This book also: Provides solutions analytically and numerically using MATLAB Illustrations and graphs generated with MATLAB reinforce visual learning for students as they study Covers modern technical advancements in areas like multibody systems, robotics, spacecraft and des...

Research based on matlab method of digital trapezoidal shaping filter

International Nuclear Information System (INIS)

Zhou Qinghua; Zhang Ruanyu; Li Taihua

2008-01-01

In order to develop digital shaping system fast and conveniently, the paper presents the method of optimizing the trapezoidal shaping filter's parameters by using MATLAB, and discusses the affections of the parameters to the shaping result by this method. (authors)

MBEToolbox: a Matlab toolbox for sequence data analysis in molecular biology and evolution

Directory of Open Access Journals (Sweden)

Xia Xuhua

2005-03-01

Full Text Available Abstract Background MATLAB is a high-performance language for technical computing, integrating computation, visualization, and programming in an easy-to-use environment. It has been widely used in many areas, such as mathematics and computation, algorithm development, data acquisition, modeling, simulation, and scientific and engineering graphics. However, few functions are freely available in MATLAB to perform the sequence data analyses specifically required for molecular biology and evolution. Results We have developed a MATLAB toolbox, called MBEToolbox, aimed at filling this gap by offering efficient implementations of the most needed functions in molecular biology and evolution. It can be used to manipulate aligned sequences, calculate evolutionary distances, estimate synonymous and nonsynonymous substitution rates, and infer phylogenetic trees. Moreover, it provides an extensible, functional framework for users with more specialized requirements to explore and analyze aligned nucleotide or protein sequences from an evolutionary perspective. The full functions in the toolbox are accessible through the command-line for seasoned MATLAB users. A graphical user interface, that may be especially useful for non-specialist end users, is also provided. Conclusion MBEToolbox is a useful tool that can aid in the exploration, interpretation and visualization of data in molecular biology and evolution. The software is publicly available at http://web.hku.hk/~jamescai/mbetoolbox/ and http://bioinformatics.org/project/?group_id=454.

Conformal Interpolating Algorithm Based on Cubic NURBS in Aspheric Ultra-Precision Machining

International Nuclear Information System (INIS)

Li, C G; Zhang, Q R; Cao, C G; Zhao, S L

2006-01-01

Numeric control machining and on-line compensation for aspheric surface are key techniques in ultra-precision machining. In this paper, conformal cubic NURBS interpolating curve is applied to fit the character curve of aspheric surface. Its algorithm and process are also proposed and imitated by Matlab7.0 software. To evaluate the performance of the conformal cubic NURBS interpolation, we compare it with the linear interpolations. The result verifies this method can ensure smoothness of interpolating spline curve and preserve original shape characters. The surface quality interpolated by cubic NURBS is higher than by line. The algorithm is benefit to increasing the surface form precision of workpieces in ultra-precision machining

Experimental study on composite solid propellant material burning rate using algorithm MATLAB

Directory of Open Access Journals (Sweden)

Thunaipragasam Selvakumaran

2016-01-01

Full Text Available In rocketry application, now-a-days instead of monopropellants slowly composite propellants are introduced. Burning rate of a solid state composite propellant depends on many factors like oxidizer-binder ratio, oxidizer particle size and distribution, particle size and its distribution, pressure, temperature, etc. Several researchers had taken the mass varied composite propellant. In that, the ammonium perchlorate mainly varied from 85 to 90%. This paper deals with the oxidizer rich propellant by allowing small variation of fuel cum binder ranging from 2%, 4%, 6%, and 8% by mass. Since the percent of the binder is very less compared to the oxidizer, the mixture remains in a powder form. The powder samples are used to make a pressed pellet. Experiments were conducted in closed window bomb set-up at pressures of 2, 3.5, and 7 MN/m2. The burning rates are calculated from the combustion photography (images taken by a high-speed camera. These images were processed frame by frame in MATLAB, detecting the edges in the images of the frames. The burning rate is obtained as the slope of the linear fit from MATLAB and observed that the burn rate increases with the mass variation of constituents present in solid state composite propellant. The result indicates a remarkable increase in burn rate of 26.66%, 20%, 16.66%, and 3.33% for Mix 1, 2, 3, 4 compared with Mix 5 at 7 MN/m2. The percentage variations in burn rate between Mix 1 and Mix 5 at 2, 3.5, and 7 MN/m2 are 25.833%, 32.322%, and 26.185%, respectively.

Matlab Tools: An Alternative to Planning Systems in Brachytherapy Treatments

International Nuclear Information System (INIS)

Herrera, Higmar; Rodriguez, Mercedes; Rodriguez, Miguel

2006-01-01

This work proposes the use of the Matlab environment to obtain the treatment dose based on the reported data by Krishnaswamy and Liu et al. The comparison with reported measurements is showed for the Amersham source model. For the 3M source model, measurements with TLDs and a Monte Carlo simulation are compared to the data obtained by Matlab. The difference for the Amersham model is well under the 15% recommended by the IAEA and for the 3M model, although the difference is greater, the results are consistent. The good agreement to the reported data allows the Matlab calculations to be used in daily brachytherapy treatments

Based on matlab 3d visualization programming in the application of the uranium exploration

International Nuclear Information System (INIS)

Qi Jianquan

2012-01-01

Combined geological theory, geophysical curve and Matlab programming three dimensional visualization applied to the production of uranium exploration. With a simple Matlab programming, numerical processing and graphical visualization of convenient features, and effective in identifying ore bodies, recourse to ore, ore body delineation of the scope of analysis has played the role of sedimentary environment. (author)

Edge detection and mathematic fitting for corneal surface with Matlab software.

Science.gov (United States)

Di, Yue; Li, Mei-Yan; Qiao, Tong; Lu, Na

2017-01-01

To select the optimal edge detection methods to identify the corneal surface, and compare three fitting curve equations with Matlab software. Fifteen subjects were recruited. The corneal images from optical coherence tomography (OCT) were imported into Matlab software. Five edge detection methods (Canny, Log, Prewitt, Roberts, Sobel) were used to identify the corneal surface. Then two manual identifying methods (ginput and getpts) were applied to identify the edge coordinates respectively. The differences among these methods were compared. Binomial curve (y=Ax 2 +Bx+C), Polynomial curve [p(x)=p1x n +p2x n-1 +....+pnx+pn+1] and Conic section (Ax 2 +Bxy+Cy 2 +Dx+Ey+F=0) were used for curve fitting the corneal surface respectively. The relative merits among three fitting curves were analyzed. Finally, the eccentricity (e) obtained by corneal topography and conic section were compared with paired t -test. Five edge detection algorithms all had continuous coordinates which indicated the edge of the corneal surface. The ordinates of manual identifying were close to the inside of the actual edges. Binomial curve was greatly affected by tilt angle. Polynomial curve was lack of geometrical properties and unstable. Conic section could calculate the tilted symmetry axis, eccentricity, circle center, etc . There were no significant differences between 'e' values by corneal topography and conic section ( t =0.9143, P =0.3760 >0.05). It is feasible to simulate the corneal surface with mathematical curve with Matlab software. Edge detection has better repeatability and higher efficiency. The manual identifying approach is an indispensable complement for detection. Polynomial and conic section are both the alternative methods for corneal curve fitting. Conic curve was the optimal choice based on the specific geometrical properties.

Linear algebra applications using Matlab software

Directory of Open Access Journals (Sweden)

Cornelia Victoria Anghel

2005-10-01

Full Text Available The paper presents two ways of special matrix generating using some functions included in the MatLab software package. The MatLab software package contains a set of functions that generate special matrixes used in the linear algebra applications and the signal processing from different activity fields. The paper presents two tipes of special matrixes that can be generated using written sintaxes in the dialog window of the MatLab software and for the command validity we need to press the Enter task. The applications presented in the paper represent eamples of numerical calculus using the MatLab software and belong to the scientific field „Computer Assisted Mathematics” thus creating the symbiosis between mathematics and informatics.

Cyclotron beam dynamic simulations in MATLAB

International Nuclear Information System (INIS)

Karamysheva, G.A.; Karamyshev, O.V.; Lepkina, O.E.

2008-01-01

MATLAB is useful for beam dynamic simulations in cyclotrons. Programming in an easy-to-use environment permits creation of models in a short space of time. Advanced graphical tools of MATLAB give good visualization features to created models. The beam dynamic modeling results with an example of two different cyclotron designs are presented. Programming with MATLAB opens wide possibilities of the development of the complex program, able to perform complete block of calculations for the design of the accelerators

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

Directory of Open Access Journals (Sweden)

Sravya Atluri

2016-10-01

Full Text Available Concurrent recording of electroencephalography (EEG during transcranial magnetic stimulation (TMS is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its wide-spread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEPs. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This paper introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive GUIs, this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides (i targeted removal of TMS-induced and general EEG artifacts, (ii a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms, (iii a comprehensive display and quantification of artifacts, (iv quality control check points with visual feedback of TEPs throughout the data processing workflow, and (v capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this paper we introduce TMSEEG, validate its features, and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline for TMS-EEG signal

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation.

Science.gov (United States)

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C; Wong, Willy; Daskalakis, Zafiris J; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline

TMSEEG: A MATLAB-Based Graphical User Interface for Processing Electrophysiological Signals during Transcranial Magnetic Stimulation

Science.gov (United States)

Atluri, Sravya; Frehlich, Matthew; Mei, Ye; Garcia Dominguez, Luis; Rogasch, Nigel C.; Wong, Willy; Daskalakis, Zafiris J.; Farzan, Faranak

2016-01-01

Concurrent recording of electroencephalography (EEG) during transcranial magnetic stimulation (TMS) is an emerging and powerful tool for studying brain health and function. Despite a growing interest in adaptation of TMS-EEG across neuroscience disciplines, its widespread utility is limited by signal processing challenges. These challenges arise due to the nature of TMS and the sensitivity of EEG to artifacts that often mask TMS-evoked potentials (TEP)s. With an increase in the complexity of data processing methods and a growing interest in multi-site data integration, analysis of TMS-EEG data requires the development of a standardized method to recover TEPs from various sources of artifacts. This article introduces TMSEEG, an open-source MATLAB application comprised of multiple algorithms organized to facilitate a step-by-step procedure for TMS-EEG signal processing. Using a modular design and interactive graphical user interface (GUI), this toolbox aims to streamline TMS-EEG signal processing for both novice and experienced users. Specifically, TMSEEG provides: (i) targeted removal of TMS-induced and general EEG artifacts; (ii) a step-by-step modular workflow with flexibility to modify existing algorithms and add customized algorithms; (iii) a comprehensive display and quantification of artifacts; (iv) quality control check points with visual feedback of TEPs throughout the data processing workflow; and (v) capability to label and store a database of artifacts. In addition to these features, the software architecture of TMSEEG ensures minimal user effort in initial setup and configuration of parameters for each processing step. This is partly accomplished through a close integration with EEGLAB, a widely used open-source toolbox for EEG signal processing. In this article, we introduce TMSEEG, validate its features and demonstrate its application in extracting TEPs across several single- and multi-pulse TMS protocols. As the first open-source GUI-based pipeline

MatchGUI: A Graphical MATLAB-Based Tool for Automatic Image Co-Registration

Science.gov (United States)

Ansar, Adnan I.

2011-01-01

MatchGUI software, based on MATLAB, automatically matches two images and displays the match result by superimposing one image on the other. A slider bar allows focus to shift between the two images. There are tools for zoom, auto-crop to overlap region, and basic image markup. Given a pair of ortho-rectified images (focused primarily on Mars orbital imagery for now), this software automatically co-registers the imagery so that corresponding image pixels are aligned. MatchGUI requires minimal user input, and performs a registration over scale and inplane rotation fully automatically

Parallelization of the model-based iterative reconstruction algorithm DIRA

International Nuclear Information System (INIS)

Oertenberg, A.; Sandborg, M.; Alm Carlsson, G.; Malusek, A.; Magnusson, M.

2016-01-01

New paradigms for parallel programming have been devised to simplify software development on multi-core processors and many-core graphical processing units (GPU). Despite their obvious benefits, the parallelization of existing computer programs is not an easy task. In this work, the use of the Open Multiprocessing (OpenMP) and Open Computing Language (OpenCL) frameworks is considered for the parallelization of the model-based iterative reconstruction algorithm DIRA with the aim to significantly shorten the code's execution time. Selected routines were parallelized using OpenMP and OpenCL libraries; some routines were converted from MATLAB to C and optimised. Parallelization of the code with the OpenMP was easy and resulted in an overall speedup of 15 on a 16-core computer. Parallelization with OpenCL was more difficult owing to differences between the central processing unit and GPU architectures. The resulting speedup was substantially lower than the theoretical peak performance of the GPU; the cause was explained. (authors)

First Steps into Practical Engineering for Freshman Students Using MATLAB and LEGO Mindstorms Robots

Directory of Open Access Journals (Sweden)

A. Behrens

2008-01-01

Full Text Available Besides lectures on basic theoretical topics, contemporary teaching and learning concepts for first semester students give more and more consideration to practically motivated courses. In this context, a new first-year introductory course in practical engineering has been established in the first semester curriculum of Electrical Engineering at RWTH Aachen University, Germany. Based on a threefold learning concept, programming skills in MATLAB are taught to 309 students within a full-time block course laboratory. The students are encouraged to transfer known mathematical basics to program algorithms and real-world applications performed by 100 LEGO Mindstorms robots. A new MATLAB toolbox and twofold project tasks have been developed for this purpose by a small team of supervisors. The students are supervised by over 60 tutors at 23 institutes, and are encouraged to create their own robotics applications. We describe how the laboratory motivates the students to act and think like engineers and to solve real-world issues with limited resources. The evaluation results show that the proposed practical course concept successfully boosts students’ motivation, advances their programming skills, and encourages the peer learning process. 

Accelerating Computation of DCM for ERP in MATLAB by External Function Calls to the GPU

Science.gov (United States)

Wang, Wei-Jen; Hsieh, I-Fan; Chen, Chun-Chuan

2013-01-01

This study aims to improve the performance of Dynamic Causal Modelling for Event Related Potentials (DCM for ERP) in MATLAB by using external function calls to a graphics processing unit (GPU). DCM for ERP is an advanced method for studying neuronal effective connectivity. DCM utilizes an iterative procedure, the expectation maximization (EM) algorithm, to find the optimal parameters given a set of observations and the underlying probability model. As the EM algorithm is computationally demanding and the analysis faces possible combinatorial explosion of models to be tested, we propose a parallel computing scheme using the GPU to achieve a fast estimation of DCM for ERP. The computation of DCM for ERP is dynamically partitioned and distributed to threads for parallel processing, according to the DCM model complexity and the hardware constraints. The performance efficiency of this hardware-dependent thread arrangement strategy was evaluated using the synthetic data. The experimental data were used to validate the accuracy of the proposed computing scheme and quantify the time saving in practice. The simulation results show that the proposed scheme can accelerate the computation by a factor of 155 for the parallel part. For experimental data, the speedup factor is about 7 per model on average, depending on the model complexity and the data. This GPU-based implementation of DCM for ERP gives qualitatively the same results as the original MATLAB implementation does at the group level analysis. In conclusion, we believe that the proposed GPU-based implementation is very useful for users as a fast screen tool to select the most likely model and may provide implementation guidance for possible future clinical applications such as online diagnosis. PMID:23840507

Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

Science.gov (United States)

Duan, Haibin; Li, Pei; Shi, Yuhui; Zhang, Xiangyin; Sun, Changhao

2015-01-01

This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the…

Perancangan Kendali Pid Dengan Matlab

OpenAIRE

Sukamta, Sri

2010-01-01

Perancangan PID Controller selama ini menggunakan metoda trial and error dengan perhitungan yangmemakan waktu lama. MatLab yang dilengkapi Control Toolbox, membantu perancang untuk melihatrespon berbagai kombinasi konstanta dengan variasi input yang berbeda. Penggunaan MatLab ini sangatmembantu perancang dalam menentukan kombinasi di antara P, I, dan D Controller untuk menghasilkansistem pengaturan yang baik dan sederhana.

‘PhysTrack’: a Matlab based environment for video tracking of kinematics in the physics laboratory

Science.gov (United States)

Umar Hassan, Muhammad; Sabieh Anwar, Muhammad

2017-07-01

In the past two decades, several computer software tools have been developed to investigate the motion of moving bodies in physics laboratories. In this article we report a Matlab based video tracking library, PhysTrack, primarily designed to investigate kinematics. We compare PhysTrack with other commonly available video tracking tools and outline its salient features. The general methodology of the whole video tracking process is described with a step by step explanation of several functionalities. Furthermore, results of some real physics experiments are also provided to demonstrate the working of the automated video tracking, data extraction, data analysis and presentation tools that come with this development environment. We believe that PhysTrack will be valuable for the large community of physics teachers and students already employing Matlab.

A Total Factor Productivity Toolbox for MATLAB

NARCIS (Netherlands)

B.M. Balk (Bert); J. Barbero (Javier); J.L. Zofío (José)

2018-01-01

textabstractTotal Factor Productivity Toolbox is a new package for MATLAB that includes functions to calculate the main Total Factor Productivity (TFP) indices and their decompositions, based on Shephard’s distance functions and using Data Envelopment Analysis (DEA) programming techniques. The

Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes

Science.gov (United States)

Grigoryan, Artyom M.

2015-03-01

In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.

Rapid BeagleBoard prototyping with MATLAB and Simulink

CERN Document Server

Qin, Fei

2013-01-01

This book is a fast-paced guide with practical, hands-on recipes which will show you how to prototype Beagleboard-based audio/video applications using Matlab/Simlink and Sourcery Codebench on a Windows host.Beagleboard Embedded Projects is great for students and academic researchers who have practical ideas and who want to build a proof-of-concept system on an embedded hardware platform quickly and efficiently. It is also useful for product design engineers who want to ratify their applications and reduce the time-to-market. It is assumed that you are familiar with Matlab/Simulink and have som

Regulation of Voltage and Frequency in Solid Oxide Fuel Cell-Based Autonomous Microgrids Using the Whales Optimisation Algorithm

Directory of Open Access Journals (Sweden)

Sajid Hussain Qazi

2018-05-01

Full Text Available This study explores the Whales Optimization Algorithm (WOA-based PI controller for regulating the voltage and frequency of an inverter-based autonomous microgrid (MG. The MG comprises two 50 kW DGs (solid oxide fuel cells, SOFCs interfaced using a power electronics-based voltage source inverter (VSI with a 120-kV conventional grid. Four PI controller schemes for the MG are implemented: (i stationary PI controller with fixed gain values (Kp and Ki, (ii PSO tuned PI controller, (iii GWO tuned PI controller, and (iv WOA tuned PI controller. The performance of these controllers is evaluated by monitoring the system voltage and frequency during the transition of MG operation mode and changes in the load. The MATLAB/SIMULINK tool is utilised to design the proposed model of grid-tied MG alongside the MATLAB m-file to apply an optimisation technique. The simulation results show that the WOA-based PI controller which optimises the control parameters, achieve 62.7% and 59% better results for voltage and frequency regulation, respectively. The eigenvalue analysis is also provided to check the stability of the proposed controller. Furthermore, the proposed system also satisfies the limits specified in IEEE-1547-2003 for voltage and frequency.

MATLAB Software Versions and Licenses for the Peregrine System |

Science.gov (United States)

High-Performance Computing | NREL MATLAB Software Versions and Licenses for the Peregrine System MATLAB Software Versions and Licenses for the Peregrine System Learn about the MATLAB software Peregrine is R2017b. Licenses MATLAB is proprietary software. As such, users have access to a limited number

Solution of the reactor point kinetics equations by MATLAB computing

Directory of Open Access Journals (Sweden)

Singh Sudhansu S.

2015-01-01

Full Text Available The numerical solution of the point kinetics equations in the presence of Newtonian temperature feedback has been a challenging issue for analyzing the reactor transients. Reactor point kinetics equations are a system of stiff ordinary differential equations which need special numerical treatments. Although a plethora of numerical intricacies have been introduced to solve the point kinetics equations over the years, some of the simple and straightforward methods still work very efficiently with extraordinary accuracy. As an example, it has been shown recently that the fundamental backward Euler finite difference algorithm with its simplicity has proven to be one of the most effective legacy methods. Complementing the back-ward Euler finite difference scheme, the present work demonstrates the application of ordinary differential equation suite available in the MATLAB software package to solve the stiff reactor point kinetics equations with Newtonian temperature feedback effects very effectively by analyzing various classic benchmark cases. Fair accuracy of the results implies the efficient application of MATLAB ordinary differential equation suite for solving the reactor point kinetics equations as an alternate method for future applications.

Accelerator Toolbox for MATLAB

International Nuclear Information System (INIS)

Terebilo, Andrei

2001-01-01

This paper introduces Accelerator Toolbox (AT)--a collection of tools to model particle accelerators and beam transport lines in the MATLAB environment. At SSRL, it has become the modeling code of choice for the ongoing design and future operation of the SPEAR 3 synchrotron light source. AT was designed to take advantage of power and simplicity of MATLAB--commercially developed environment for technical computing and visualization. Many examples in this paper illustrate the advantages of the AT approach and contrast it with existing accelerator code frameworks

A hybrid algorithm for instant optimization of beam weights in anatomy-based intensity modulated radiotherapy: a performance evaluation study

International Nuclear Information System (INIS)

Vaitheeswaran, Ranganathan; Sathiya Narayanan, V.K.; Bhangle, Janhavi R.; Nirhali, Amit; Kumar, Namita; Basu, Sumit; Maiya, Vikram

2011-01-01

The study aims to introduce a hybrid optimization algorithm for anatomy-based intensity modulated radiotherapy (AB-IMRT). Our proposal is that by integrating an exact optimization algorithm with a heuristic optimization algorithm, the advantages of both the algorithms can be combined, which will lead to an efficient global optimizer solving the problem at a very fast rate. Our hybrid approach combines Gaussian elimination algorithm (exact optimizer) with fast simulated annealing algorithm (a heuristic global optimizer) for the optimization of beam weights in AB-IMRT. The algorithm has been implemented using MATLAB software. The optimization efficiency of the hybrid algorithm is clarified by (i) analysis of the numerical characteristics of the algorithm and (ii) analysis of the clinical capabilities of the algorithm. The numerical and clinical characteristics of the hybrid algorithm are compared with Gaussian elimination method (GEM) and fast simulated annealing (FSA). The numerical characteristics include convergence, consistency, number of iterations and overall optimization speed, which were analyzed for the respective cases of 8 patients. The clinical capabilities of the hybrid algorithm are demonstrated in cases of (a) prostate and (b) brain. The analyses reveal that (i) the convergence speed of the hybrid algorithm is approximately three times higher than that of FSA algorithm (ii) the convergence (percentage reduction in the cost function) in hybrid algorithm is about 20% improved as compared to that in GEM algorithm (iii) the hybrid algorithm is capable of producing relatively better treatment plans in terms of Conformity Index (CI) (∼ 2% - 5% improvement) and Homogeneity Index (HI) (∼ 4% - 10% improvement) as compared to GEM and FSA algorithms (iv) the sparing of organs at risk in hybrid algorithm-based plans is better than that in GEM-based plans and comparable to that in FSA-based plans; and (v) the beam weights resulting from the hybrid algorithm are

Matlab/Simulink Implementation of Wave-based Models for Microstrip Structures utilizing Short-circuited and Opened Stubs

Directory of Open Access Journals (Sweden)

Biljana P. Stošić

2011-12-01

Full Text Available This paper describes modeling and analyzing procedures for microstrip filters based on use of one-dimensional wave digital approach. Different filter structures are observed. One filter is based on quarter-wave length short-circuited stubs and connecting transmission lines. The other one is based on cross-junction opened stubs. Frequency responses are obtained by direct analysis of the block-based networks formed in Simulink toolbox of MATLAB environment. This wave-based method allows an accurate and efficient analysis of different microwave structures.

Une introduction à MATLAB c

OpenAIRE

CREMONA, Christian; LABORATOIRE CENTRAL DES PONTS ET CHAUSSEES - LCPC

2002-01-01

MATLAB c présente toutes les fonctionnalités des approches récentes de la programmation : programmation objet basée sur des hiérarchies de classes, programmation événementielle du graphisme. MATLAB c présente une aide en ligne très complète sous format html des différentes fontions accessibles. COMPTE RENDU DE RECHERCHE

Test Generator for MATLAB Simulations

Science.gov (United States)

Henry, Joel

2011-01-01

MATLAB Automated Test Tool, version 3.0 (MATT 3.0) is a software package that provides automated tools that reduce the time needed for extensive testing of simulation models that have been constructed in the MATLAB programming language by use of the Simulink and Real-Time Workshop programs. MATT 3.0 runs on top of the MATLAB engine application-program interface to communicate with the Simulink engine. MATT 3.0 automatically generates source code from the models, generates custom input data for testing both the models and the source code, and generates graphs and other presentations that facilitate comparison of the outputs of the models and the source code for the same input data. Context-sensitive and fully searchable help is provided in HyperText Markup Language (HTML) format.

Fuzzy-Based Hybrid Control Algorithm for the Stabilization of a Tri-Rotor UAV.

Science.gov (United States)

Ali, Zain Anwar; Wang, Daobo; Aamir, Muhammad

2016-05-09

In this paper, a new and novel mathematical fuzzy hybrid scheme is proposed for the stabilization of a tri-rotor unmanned aerial vehicle (UAV). The fuzzy hybrid scheme consists of a fuzzy logic controller, regulation pole-placement tracking (RST) controller with model reference adaptive control (MRAC), in which adaptive gains of the RST controller are being fine-tuned by a fuzzy logic controller. Brushless direct current (BLDC) motors are installed in the triangular frame of the tri-rotor UAV, which helps maintain control on its motion and different altitude and attitude changes, similar to rotorcrafts. MRAC-based MIT rule is proposed for system stability. Moreover, the proposed hybrid controller with nonlinear flight dynamics is shown in the presence of translational and rotational velocity components. The performance of the proposed algorithm is demonstrated via MATLAB simulations, in which the proposed fuzzy hybrid controller is compared with the existing adaptive RST controller. It shows that our proposed algorithm has better transient performance with zero steady-state error, and fast convergence towards stability.

One hundred physics visualizations using Matlab

CERN Document Server

Green, Dan

2014-01-01

This book provides visualizations of many topics in general physics. The aim is to have an interactive MATLAB script wherein the user can vary parameters in a specific problem and then immediately see the outcome by way of dynamic movies of the response of the system in question. MATLAB tools are used throughout and the software scripts accompany the text in Symbolic Mathematics, Classical Mechanics, Electromagnetism, Waves and Optics, Gases and Fluid Flow, Quantum Mechanics, Special and General Relativity, and Astrophysics and Cosmology. The emphasis is on building up an intuition by running many different parametric choices chosen actively by the user and watching the subsequent behavior of the system. Physics books using MATLAB do not have the range or the intent of this text. They are rather steeped in technical detail. Symbolic math is used extensively and is integral to the aim of using MATLAB tools to accomplish the technical aspects of problem solving.

Speed and Displacement Control System of Bearingless Brushless DC Motor Based on Improved Bacterial Foraging Algorithm

Directory of Open Access Journals (Sweden)

Diao Xiaoyan

2016-01-01

Full Text Available To solve the deficiencies of long optimization time and poor precision existing in conventional bacterial foraging algorithm (BFA in the process of parameter optimization, an improved bacterial foraging algorithm (IBFA is proposed and applied to speed and displacement control system of bearingless brushless DC (Bearingless BLDC motors. To begin with the fundamental principle of BFA, the proposed method is introduced and the individual intelligence is efficiently used in the process of parameter optimization, and then the working principle of bearingless BLDC motors is expounded. Finally, modeling and simulation of the speed and displacement control system of bearingless BLDC motors based on the IBFA are carried out by taking the software of MATLAB/Simulink as a platform. Simulation results show that, speed overshoot, torque ripple and rotor position oscillation are dramatically reduced, thus the proposed method has good application prospects in the field of bearingless motors.

Efficient Matlab Programs

Data.gov (United States)

National Aeronautics and Space Administration — Matlab has a reputation for running slowly. Here are some pointers on how to speed computations, to an often unexpected degree. Subjects currently covered: Matrix...

[Landmark-based automatic registration of serial cross-sectional images of Chinese digital human using Photoshop and Matlab software].

Science.gov (United States)

Su, Xiu-yun; Pei, Guo-xian; Yu, Bin; Hu, Yan-ling; Li, Jin; Huang, Qian; Li, Xu; Zhang, Yuan-zhi

2007-12-01

This paper describes automatic registration of the serial cross-sectional images of Chinese digital human by projective registration method based on the landmarks using the commercially available software Photoshop and Matlab. During cadaver embedment for acquisition of the Chinese digital human images, 4 rods were placed parallel to the vertical axis of the frozen cadaver to allow orientation. Projective distortion of the rod positions on the cross-sectional images was inevitable due to even slight changes of the relative position of the camera. The original cross-sectional images were first processed using Photoshop software firstly to obtain the images of the orientation rods, and the centroid coordinate of every rod image was acquired with Matlab software. With the average coordinate value of the rods as the fiducial point, two-dimensional projective transformation coefficient of each image was determined. Projective transformation was then carried out and projective distortion from each original serial image was eliminated. The rectified cross-sectional images were again processed using Photoshop to obtain the image of the first orientation rod, the coordinate value of first rod image was calculated using Matlab software, and the cross-sectional images were cut into images of the same size according to the first rod spatial coordinate, to achieve automatic registration of the serial cross-sectional images. sing Photoshop and Matlab softwares, projective transformation can accurately accomplish the image registration for the serial images with simpler calculation processes and easier computer processing.

MATLAB as a tool as Analysis and Problem Solving Competency Development in Chemical Engineering Degree using MATLAB

Directory of Open Access Journals (Sweden)

Maria-Fernanda López-Pérez

2016-10-01

The principal purpose of this work is the students improvement using, as has been mentioned previously, MATLAB in a problem-based learning methodology. This methodology allows a more effective coordination in the degree. The present paper presents a real- world problem and the common elements of most problem-solving contexts and how is designed to function across all disciplines.

Automated Photogrammetric Image Matching with Sift Algorithm and Delaunay Triangulation

DEFF Research Database (Denmark)

Karagiannis, Georgios; Antón Castro, Francesc/François; Mioc, Darka

2016-01-01

An algorithm for image matching of multi-sensor and multi-temporal satellite images is developed. The method is based on the SIFT feature detector proposed by Lowe in (Lowe, 1999). First, SIFT feature points are detected independently in two images (reference and sensed image). The features detec...... of each feature set for each image are computed. The isomorphism of the Delaunay triangulations is determined to guarantee the quality of the image matching. The algorithm is implemented in Matlab and tested on World-View 2, SPOT6 and TerraSAR-X image patches....

Firefly algorithm based solution to minimize the real power loss in a power system

Directory of Open Access Journals (Sweden)

P. Balachennaiah

2018-03-01

Full Text Available This paper proposes a method to minimize the real power loss (RPL of a power system transmission network using a new meta-heuristic algorithm known as firefly algorithm (FA by optimizing the control variables such as transformer taps, UPFC location and UPFC series injected voltage magnitude and phase angle. A software program is developed in MATLAB environment for FA to minimize the RPL by optimizing (i only the transformer tap values, (ii only UPFC location and its variables with optimized tap values and (iii UPFC location and its variables along with transformer tap setting values simultaneously. Interior point successive linear programming (IPSLP technique and real coded genetic algorithm (RCGA are considered here to compare the results and to show the efficiency and superiority of the proposed FA towards the optimization of RPL. Also in this paper, bacteria foraging algorithm (BFA is adopted to validate the results of the proposed algorithm.

Use of trapezoidal shaping algorithm in the digital multi-channel system

International Nuclear Information System (INIS)

Wang Jihong; Wang Lianghou; Fang Zongliang

2011-01-01

It discusses one kind of digital filter technology-trapezoidal algorithm based on actual need of studying the digital multi-channel. Firstly, demonstrating the feasibility of the arithmetic with theoretical analysis; secondly, predigesting the process of the arithmetic; thirdly, simulating with MATLAB; lastly, using the arithmetic to measure data. The result of testing indicates trapezoidal shaping algorithm accords with the need of digital multi-channel shaping extraordinary. The best filter can be obtained by means of setting parameter due to superiority of digital multi-channel. (authors)

Design a software real-time operation platform for wave piercing catamarans motion control using linear quadratic regulator based genetic algorithm.

Science.gov (United States)

Liang, Lihua; Yuan, Jia; Zhang, Songtao; Zhao, Peng

2018-01-01

This work presents optimal linear quadratic regulator (LQR) based on genetic algorithm (GA) to solve the two degrees of freedom (2 DoF) motion control problem in head seas for wave piercing catamarans (WPC). The proposed LQR based GA control strategy is to select optimal weighting matrices (Q and R). The seakeeping performance of WPC based on proposed algorithm is challenged because of multi-input multi-output (MIMO) system of uncertain coefficient problems. Besides the kinematical constraint problems of WPC, the external conditions must be considered, like the sea disturbance and the actuators (a T-foil and two flaps) control. Moreover, this paper describes the MATLAB and LabVIEW software plats to simulate the reduction effects of WPC. Finally, the real-time (RT) NI CompactRIO embedded controller is selected to test the effectiveness of the actuators based on proposed techniques. In conclusion, simulation and experimental results prove the correctness of the proposed algorithm. The percentage of heave and pitch reductions are more than 18% in different high speeds and bad sea conditions. And the results also verify the feasibility of NI CompactRIO embedded controller.

NNCTRL - a CANCSD toolkit for MATLAB(R)

DEFF Research Database (Denmark)

Nørgård, Peter Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

1996-01-01

A set of tools for computer-aided neuro-control system design (CANCSD) has been developed for the MATLAB environment. The tools can be used for construction and simulation of a variety of neural network based control systems. The design methods featured in the toolkit are: direct inverse control...

Adaptive algorithm of magnetic heading detection

Science.gov (United States)

Liu, Gong-Xu; Shi, Ling-Feng

2017-11-01

Magnetic data obtained from a magnetic sensor usually fluctuate in a certain range, which makes it difficult to estimate the magnetic heading accurately. In fact, magnetic heading information is usually submerged in noise because of all kinds of electromagnetic interference and the diversity of the pedestrian’s motion states. In order to solve this problem, a new adaptive algorithm based on the (typically) right-angled corridors of a building or residential buildings is put forward to process heading information. First, a 3D indoor localization platform is set up based on MPU9250. Then, several groups of data are measured by changing the experimental environment and pedestrian’s motion pace. The raw data from the attached inertial measurement unit are calibrated and arranged into a time-stamped array and written to a data file. Later, the data file is imported into MATLAB for processing and analysis using the proposed adaptive algorithm. Finally, the algorithm is verified by comparison with the existing algorithm. The experimental results show that the algorithm has strong robustness and good fault tolerance, which can detect the heading information accurately and in real-time.

A Refined Self-Tuning Filter-Based Instantaneous Power Theory Algorithm for Indirect Current Controlled Three-Level Inverter-Based Shunt Active Power Filters under Non-sinusoidal Source Voltage Conditions

Directory of Open Access Journals (Sweden)

Yap Hoon

2017-02-01

Full Text Available In this paper, a refined reference current generation algorithm based on instantaneous power (pq theory is proposed, for operation of an indirect current controlled (ICC three-level neutral-point diode clamped (NPC inverter-based shunt active power filter (SAPF under non-sinusoidal source voltage conditions. SAPF is recognized as one of the most effective solutions to current harmonics due to its flexibility in dealing with various power system conditions. As for its controller, pq theory has widely been applied to generate the desired reference current due to its simple implementation features. However, the conventional dependency on self-tuning filter (STF in generating reference current has significantly limited mitigation performance of SAPF. Besides, the conventional STF-based pq theory algorithm is still considered to possess needless features which increase computational complexity. Furthermore, the conventional algorithm is mostly designed to suit operation of direct current controlled (DCC SAPF which is incapable of handling switching ripples problems, thereby leading to inefficient mitigation performance. Therefore, three main improvements are performed which include replacement of STF with mathematical-based fundamental real power identifier, removal of redundant features, and generation of sinusoidal reference current. To validate effectiveness and feasibility of the proposed algorithm, simulation work in MATLAB-Simulink and laboratory test utilizing a TMS320F28335 digital signal processor (DSP are performed. Both simulation and experimental findings demonstrate superiority of the proposed algorithm over the conventional algorithm.

Menhir: An Environment for High Performance Matlab

Directory of Open Access Journals (Sweden)

Stéphane Chauveau

1999-01-01

Full Text Available In this paper we present Menhir a compiler for generating sequential or parallel code from the Matlab language. The compiler has been designed in the context of using Matlab as a specification language. One of the major features of Menhir is its retargetability to generate parallel and sequential C or Fortran code. We present the compilation process and the target system description for Menhir. Preliminary performances are given and compared with MCC, the MathWorks Matlab compiler.

Biomedical image analysis recipes in Matlab for life scientists and engineers

CERN Document Server

Reyes-Aldasoro, Constantino Carlos

2015-01-01

As its title suggests, this innovative book has been written for life scientists needing to analyse their data sets, and programmers, wanting a better understanding of the types of experimental images life scientists investigate on a regular basis. Each chapter presents one self-contained biomedical experiment to be analysed. Part I of the book presents its two basic ingredients: essential concepts of image analysis and Matlab. In Part II, algorithms and techniques are shown as series of 'recipes' or solved examples that show how specific techniques are applied to a biomedical experiments like

A Compression Algorithm in Wireless Sensor Networks of Bearing Monitoring

International Nuclear Information System (INIS)

Zheng Bin; Meng Qingfeng; Wang Nan; Li Zhi

2011-01-01

The energy consumption of wireless sensor networks (WSNs) is always an important problem in the application of wireless sensor networks. This paper proposes a data compression algorithm to reduce amount of data and energy consumption during the data transmission process in the on-line WSNs-based bearing monitoring system. The proposed compression algorithm is based on lifting wavelets, Zerotree coding and Hoffman coding. Among of that, 5/3 lifting wavelets is used for dividing data into different frequency bands to extract signal characteristics. Zerotree coding is applied to calculate the dynamic thresholds to retain the attribute data. The attribute data are then encoded by Hoffman coding to further enhance the compression ratio. In order to validate the algorithm, simulation is carried out by using Matlab. The result of simulation shows that the proposed algorithm is very suitable for the compression of bearing monitoring data. The algorithm has been successfully used in online WSNs-based bearing monitoring system, in which TI DSP TMS320F2812 is used to realize the algorithm.

Image enhancement using MCNP5 code and MATLAB in neutron radiography

International Nuclear Information System (INIS)

Tharwat, Montaser; Mohamed, Nader; Mongy, T.

2014-01-01

This work presents a method that can be used to enhance the neutron radiography (NR) image for objects with high scattering materials like hydrogen, carbon and other light materials. This method used Monte Carlo code, MCNP5, to simulate the NR process and get the flux distribution for each pixel of the image and determines the scattered neutron distribution that caused image blur, and then uses MATLAB to subtract this scattered neutron distribution from the initial image to improve its quality. This work was performed before the commissioning of digital NR system in Jan. 2013. The MATLAB enhancement method is quite a good technique in the case of static based film neutron radiography, while in neutron imaging (NI) technique, image enhancement and quantitative measurement were efficient by using ImageJ software. The enhanced image quality and quantitative measurements were presented in this work. - Highlights: • This work is applicable for static based film neutron radiography and digital neutron imaging. • MATLAB is a useful tool for imaging enhancement in radiographic film. • Advanced imaging processing is available in the ETRR-2 for imaging processing and data extraction. • The digital imaging system is suitable for complex shapes and sizes, while MATLAB technique is suitable for simple shapes and sizes. • Quantitative measurements are available

KEGGParser: parsing and editing KEGG pathway maps in Matlab.

Science.gov (United States)

Arakelyan, Arsen; Nersisyan, Lilit

2013-02-15

KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab. The source code is available at http://www.mathworks.com/matlabcentral/fileexchange/37561.

Fuzzy logic based control system for fresh water aquaculture: A MATLAB based simulation approach

Directory of Open Access Journals (Sweden)

Rana Dinesh Singh

2015-01-01

Full Text Available Fuzzy control is regarded as the most widely used application of fuzzy logic. Fuzzy logic is an innovative technology to design solutions for multiparameter and non-linear control problems. One of the greatest advantages of fuzzy control is that it uses human experience and process information obtained from operator rather than a mathematical model for the definition of a control strategy. As a result, it often delivers solutions faster than conventional control design techniques. The proposed system is an attempt to apply fuzzy logic techniques to predict the stress factor on the fish, based on line data and rule base generated using domain expert. The proposed work includes a use of Data acquisition system, an interfacing device for on line parameter acquisition and analysis, fuzzy logic controller (FLC for inferring the stress factor. The system takes stress parameters on the fish as inputs, fuzzified by using FLC with knowledge base rules and finally provides single output. All the parameters are controlled and calibrated by the fuzzy logic toolbox and MATLAB programming.

Digital signal processing with Matlab examples

CERN Document Server

Giron-Sierra, Jose Maria

2017-01-01

This is the first volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed. The book is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.

Artificial Immune Algorithm for Subtask Industrial Robot Scheduling in Cloud Manufacturing

Science.gov (United States)

Suma, T.; Murugesan, R.

2018-04-01

The current generation of manufacturing industry requires an intelligent scheduling model to achieve an effective utilization of distributed manufacturing resources, which motivated us to work on an Artificial Immune Algorithm for subtask robot scheduling in cloud manufacturing. This scheduling model enables a collaborative work between the industrial robots in different manufacturing centers. This paper discussed two optimizing objectives which includes minimizing the cost and load balance of industrial robots through scheduling. To solve these scheduling problems, we used the algorithm based on Artificial Immune system. The parameters are simulated with MATLAB and the results compared with the existing algorithms. The result shows better performance than existing.

Modeling of serial data acquisition structure for GEM detector system in Matlab

Science.gov (United States)

Kolasinski, Piotr; Pozniak, Krzysztof T.; Czarski, Tomasz; Chernyshova, Maryna; Kasprowicz, Grzegorz; Krawczyk, Rafal D.; Wojenski, Andrzej; Zabolotny, Wojciech; Byszuk, Adrian

2016-09-01

This article presents method of modeling in Matlab hardware architecture dedicated for FPGA created by languages like VHDL or Verilog. Purposes of creating such type of model with its advantages and disadvantages are described. Rules presented in this article were exploited to create model of Serial Data Acquisition algorithm used in X-ray GEM detector system. Result were compared to real working model implemented in VHDL. After testing of basic structure, other two structures were modeled to see influence parameters of the structure on its behavior.

PM Synchronous Motor Dynamic Modeling with Genetic Algorithm ...

African Journals Online (AJOL)

Adel

This paper proposes dynamic modeling simulation for ac Surface Permanent Magnet Synchronous ... Simulations are implemented using MATLAB with its genetic algorithm toolbox. .... selection, the process that drives biological evolution.

A guide to MATLAB for beginners and experienced users

CERN Document Server

Hunt, Brian R; Rosenberg, Jonathan M

2014-01-01

Now in its third edition, this outstanding textbook explains everything you need to get started using MATLAB®. It contains concise explanations of essential MATLAB commands, as well as easily understood instructions for using MATLAB's programming features, graphical capabilities, simulation models, and rich desktop interface. MATLAB 8 and its new user interface is treated extensively in the book. New features in this edition include: a complete treatment of MATLAB's publish feature; new material on MATLAB graphics, enabling the user to master quickly the various symbolic and numerical plotting routines; and a robust presentation of MuPAD® and how to use it as a stand-alone platform. The authors have also updated the text throughout, reworking examples and exploring new applications. The book is essential reading for beginners, occasional users and experienced users wishing to brush up their skills. Further resources are available from the authors' website at www-math.umd.edu/schol/a-guide-to-matlab.html.

Curtain Antenna Array Simulation Research Based on MATLAB

Directory of Open Access Journals (Sweden)

Hongbo LIU

2014-01-01

Full Text Available For the radiating capacity of curtain antenna array, this paper constructs a three- line-four-column curtain antenna array using cage antenna as the antenna array element and obtains a normalizing 3D radiation patterns through conducting simulation with MATLAB. Meanwhile, the relationships between the antenna spacing and the largest directivity coefficient, as well as the communication frequency and largest directivity coefficient are analyzed in this paper. It turns out that the max value will generate when the antenna spacing is around 18 m and the best communication effect will be achieved when the communication frequency is about 12.4 MHz.

Computational colour science using MATLAB

CERN Document Server

Westland, Stephen; Cheung, Vien

2012-01-01

Computational Colour Science Using MATLAB 2nd Edition offers a practical, problem-based approach to colour physics. The book focuses on the key issues encountered in modern colour engineering, including efficient representation of colour information, Fourier analysis of reflectance spectra and advanced colorimetric computation. Emphasis is placed on the practical applications rather than the techniques themselves, with material structured around key topics. These topics include colour calibration of visual displays, computer recipe prediction and models for colour-appearance prediction. Each t

A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders

2015-01-01

We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...

Optimized Aircraft Electric Control System Based on Adaptive Tabu Search Algorithm and Fuzzy Logic Control

Directory of Open Access Journals (Sweden)

Saifullah Khalid

2016-09-01

Full Text Available Three conventional control constant instantaneous power control, sinusoidal current control, and synchronous reference frame techniques for extracting reference currents for shunt active power filters have been optimized using Fuzzy Logic control and Adaptive Tabu search Algorithm and their performances have been compared. Critical analysis of Comparison of the compensation ability of different control strategies based on THD and speed will be done, and suggestions will be given for the selection of technique to be used. The simulated results using MATLAB model are presented, and they will clearly prove the value of the proposed control method of aircraft shunt APF. The waveforms observed after the application of filter will be having the harmonics within the limits and the power quality will be improved.

MATLAB for Engineering and the Life Sciences

CERN Document Server

Tranquillo, Joseph

2011-01-01

In recent years, the life sciences have embraced simulation as an important tool in biomedical research. Engineers are also using simulation as a powerful step in the design process. In both arenas, Matlab has become the gold standard. It is easy to learn, flexible, and has a large and growing userbase. MATLAB for Engineering and the Life Sciences is a self-guided tour of the basic functionality of MATLAB along with the functions that are most commonly used in biomedical engineering and other life sciences. Although the text is written for undergraduates, graduate students and academics, those

A proposed adaptive step size perturbation and observation maximum power point tracking algorithm based on photovoltaic system modeling

Science.gov (United States)

Huang, Yu

Solar energy becomes one of the major alternative renewable energy options for its huge abundance and accessibility. Due to the intermittent nature, the high demand of Maximum Power Point Tracking (MPPT) techniques exists when a Photovoltaic (PV) system is used to extract energy from the sunlight. This thesis proposed an advanced Perturbation and Observation (P&O) algorithm aiming for relatively practical circumstances. Firstly, a practical PV system model is studied with determining the series and shunt resistances which are neglected in some research. Moreover, in this proposed algorithm, the duty ratio of a boost DC-DC converter is the object of the perturbation deploying input impedance conversion to achieve working voltage adjustment. Based on the control strategy, the adaptive duty ratio step size P&O algorithm is proposed with major modifications made for sharp insolation change as well as low insolation scenarios. Matlab/Simulink simulation for PV model, boost converter control strategy and various MPPT process is conducted step by step. The proposed adaptive P&O algorithm is validated by the simulation results and detail analysis of sharp insolation changes, low insolation condition and continuous insolation variation.

Widely applicable MATLAB routines for automated analysis of saccadic reaction times.

Science.gov (United States)

Leppänen, Jukka M; Forssman, Linda; Kaatiala, Jussi; Yrttiaho, Santeri; Wass, Sam

2015-06-01

Saccadic reaction time (SRT) is a widely used dependent variable in eye-tracking studies of human cognition and its disorders. SRTs are also frequently measured in studies with special populations, such as infants and young children, who are limited in their ability to follow verbal instructions and remain in a stable position over time. In this article, we describe a library of MATLAB routines (Mathworks, Natick, MA) that are designed to (1) enable completely automated implementation of SRT analysis for multiple data sets and (2) cope with the unique challenges of analyzing SRTs from eye-tracking data collected from poorly cooperating participants. The library includes preprocessing and SRT analysis routines. The preprocessing routines (i.e., moving median filter and interpolation) are designed to remove technical artifacts and missing samples from raw eye-tracking data. The SRTs are detected by a simple algorithm that identifies the last point of gaze in the area of interest, but, critically, the extracted SRTs are further subjected to a number of postanalysis verification checks to exclude values contaminated by artifacts. Example analyses of data from 5- to 11-month-old infants demonstrated that SRTs extracted with the proposed routines were in high agreement with SRTs obtained manually from video records, robust against potential sources of artifact, and exhibited moderate to high test-retest stability. We propose that the present library has wide utility in standardizing and automating SRT-based cognitive testing in various populations. The MATLAB routines are open source and can be downloaded from http://www.uta.fi/med/icl/methods.html .

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

Science.gov (United States)

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a

A computerized glow curve analysis (GCA) method for WinREMS thermoluminescent dosimeter data using MATLAB

International Nuclear Information System (INIS)

Harvey, John A.; Rodrigues, Miesher L.; Kearfott, Kimberlee J.

2011-01-01

A computerized glow curve analysis (GCA) program for handling of thermoluminescence data originating from WinREMS is presented. The MATLAB program fits the glow peaks using the first-order kinetics model. Tested materials are LiF:Mg,Ti, CaF 2 :Dy, CaF 2 :Tm, CaF 2 :Mn, LiF:Mg,Cu,P, and CaSO 4 :Dy, with most having an average figure of merit (FOM) of 1.3% or less, with CaSO 4 :Dy 2.2% or less. Output is a list of fit parameters, peak areas, and graphs for each fit, evaluating each glow curve in 1.5 s or less. - Highlights: → Robust algorithm for performing thermoluminescent dosimeter glow curve analysis. → Written in MATLAB so readily implemented on variety of computers. → Usage of figure of merit demonstrated for six different materials.

An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave

Directory of Open Access Journals (Sweden)

Ikaro Silva

2014-09-01

Full Text Available The WaveForm DataBase (WFDB Toolbox for MATLAB/Octave enables  integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox allows direct loading into MATLAB/Octave's workspace of over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by meta data such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

An Accelerator control middle layer using Matlab

CERN Document Server

Portmann, G J; Terebilo, Andrei

2005-01-01

Matlab is a matrix manipulation language originally developed to be a convenient language for using the LINPACK and EISPACK libraries. What makes Matlab so appealing for accelerator physics is the combination of a matrix oriented programming language, an active workspace for system variables, powerful graphics capability, built-in math libraries, and platform independence. A number of software toolboxes for accelerators have been written in Matlab – the Accelerator Toolbox (AT) for machine simulations, LOCO for accelerator calibration, Matlab Channel Access Toolbox (MCA) for EPICS connections, and the Middle Layer. This paper will describe the MiddleLayer software toolbox that resides between the high-level control applications and the low-level accelerator control system. This software was a collaborative effort between ALS and Spear but was written to easily port. Five accelerators presently use this software – Spear, ALS, CLS, and the X-ray and VUV rings at Brookhaven. The Middle Layer fu...

Image processing and pattern recognition with CVIPtools MATLAB toolbox: automatic creation of masks for veterinary thermographic images

Science.gov (United States)

Mishra, Deependra K.; Umbaugh, Scott E.; Lama, Norsang; Dahal, Rohini; Marino, Dominic J.; Sackman, Joseph

2016-09-01

CVIPtools is a software package for the exploration of computer vision and image processing developed in the Computer Vision and Image Processing Laboratory at Southern Illinois University Edwardsville. CVIPtools is available in three variants - a) CVIPtools Graphical User Interface, b) CVIPtools C library and c) CVIPtools MATLAB toolbox, which makes it accessible to a variety of different users. It offers students, faculty, researchers and any user a free and easy way to explore computer vision and image processing techniques. Many functions have been implemented and are updated on a regular basis, the library has reached a level of sophistication that makes it suitable for both educational and research purposes. In this paper, the detail list of the functions available in the CVIPtools MATLAB toolbox are presented and how these functions can be used in image analysis and computer vision applications. The CVIPtools MATLAB toolbox allows the user to gain practical experience to better understand underlying theoretical problems in image processing and pattern recognition. As an example application, the algorithm for the automatic creation of masks for veterinary thermographic images is presented.

Matlab based Toolkits used to Interface with Optical Design Software for NASA's James Webb Space Telescope

Science.gov (United States)

Howard, Joseph

2007-01-01

The viewgraph presentation provides an introduction to the James Webb Space Telescope (JWST). The first part provides a brief overview of Matlab toolkits including CodeV, OSLO, and Zemax Toolkits. The toolkit overview examines purpose, layout, how Matlab gets data from CodeV, function layout, and using cvHELP. The second part provides examples of use with JWST, including wavefront sensitivities and alignment simulations.

SU-E-T-37: A GPU-Based Pencil Beam Algorithm for Dose Calculations in Proton Radiation Therapy

International Nuclear Information System (INIS)

Kalantzis, G; Leventouri, T; Tachibana, H; Shang, C

2015-01-01

Purpose: Recent developments in radiation therapy have been focused on applications of charged particles, especially protons. Over the years several dose calculation methods have been proposed in proton therapy. A common characteristic of all these methods is their extensive computational burden. In the current study we present for the first time, to our best knowledge, a GPU-based PBA for proton dose calculations in Matlab. Methods: In the current study we employed an analytical expression for the protons depth dose distribution. The central-axis term is taken from the broad-beam central-axis depth dose in water modified by an inverse square correction while the distribution of the off-axis term was considered Gaussian. The serial code was implemented in MATLAB and was launched on a desktop with a quad core Intel Xeon X5550 at 2.67GHz with 8 GB of RAM. For the parallelization on the GPU, the parallel computing toolbox was employed and the code was launched on a GTX 770 with Kepler architecture. The performance comparison was established on the speedup factors. Results: The performance of the GPU code was evaluated for three different energies: low (50 MeV), medium (100 MeV) and high (150 MeV). Four square fields were selected for each energy, and the dose calculations were performed with both the serial and parallel codes for a homogeneous water phantom with size 300×300×300 mm3. The resolution of the PBs was set to 1.0 mm. The maximum speedup of ∼127 was achieved for the highest energy and the largest field size. Conclusion: A GPU-based PB algorithm for proton dose calculations in Matlab was presented. A maximum speedup of ∼127 was achieved. Future directions of the current work include extension of our method for dose calculation in heterogeneous phantoms

Comparison of Pilot Symbol Embedded Channel Estimation Algorithms

Directory of Open Access Journals (Sweden)

P. Kadlec

2009-12-01

Full Text Available In the paper, algorithms of the pilot symbol embedded channel estimation are compared. Attention is turned to the Least Square (LS channel estimation and the Sliding Correlator (SC algorithm. Both algorithms are implemented in Matlab to estimate the Channel Impulse Response (CIR of a channel exhibiting multi-path propagation. Algorithms are compared from the viewpoint of computational demands, influence of the Additive White Gaussian Noise (AWGN, an embedded pilot symbol and a computed CIR over the estimation error.

The Type-2 Fuzzy Logic Controller-Based Maximum Power Point Tracking Algorithm and the Quadratic Boost Converter for Pv System

Science.gov (United States)

Altin, Necmi

2018-05-01

An interval type-2 fuzzy logic controller-based maximum power point tracking algorithm and direct current-direct current (DC-DC) converter topology are proposed for photovoltaic (PV) systems. The proposed maximum power point tracking algorithm is designed based on an interval type-2 fuzzy logic controller that has an ability to handle uncertainties. The change in PV power and the change in PV voltage are determined as inputs of the proposed controller, while the change in duty cycle is determined as the output of the controller. Seven interval type-2 fuzzy sets are determined and used as membership functions for input and output variables. The quadratic boost converter provides high voltage step-up ability without any reduction in performance and stability of the system. The performance of the proposed system is validated through MATLAB/Simulink simulations. It is seen that the proposed system provides high maximum power point tracking speed and accuracy even for fast changing atmospheric conditions and high voltage step-up requirements.

Methodology for creating dedicated machine and algorithm on sunflower counting

Science.gov (United States)

Muracciole, Vincent; Plainchault, Patrick; Mannino, Maria-Rosaria; Bertrand, Dominique; Vigouroux, Bertrand

2007-09-01

In order to sell grain lots in European countries, seed industries need a government certification. This certification requests purity testing, seed counting in order to quantify specified seed species and other impurities in lots, and germination testing. These analyses are carried out within the framework of international trade according to the methods of the International Seed Testing Association. Presently these different analyses are still achieved manually by skilled operators. Previous works have already shown that seeds can be characterized by around 110 visual features (morphology, colour, texture), and thus have presented several identification algorithms. Until now, most of the works in this domain are computer based. The approach presented in this article is based on the design of dedicated electronic vision machine aimed to identify and sort seeds. This machine is composed of a FPGA (Field Programmable Gate Array), a DSP (Digital Signal Processor) and a PC bearing the GUI (Human Machine Interface) of the system. Its operation relies on the stroboscopic image acquisition of a seed falling in front of a camera. A first machine was designed according to this approach, in order to simulate all the vision chain (image acquisition, feature extraction, identification) under the Matlab environment. In order to perform this task into dedicated hardware, all these algorithms were developed without the use of the Matlab toolbox. The objective of this article is to present a design methodology for a special purpose identification algorithm based on distance between groups into dedicated hardware machine for seed counting.

Stability Analysis of Tunnel-Slope Coupling Based on Genetic Algorithm

Directory of Open Access Journals (Sweden)

Tao Luo

2015-07-01

Full Text Available Subjects in tunnels, being constrained by terrain and routes, entrances and exits to tunnels, usually stay in the terrain with slopes. Thus, it is necessary to carry out stability analysis by treating the tunnel slope as an entity. In this study, based on the Janbu slices method, a model for the calculation of the stability of the original slope-tunnel-bank slope is established. The genetic algorithm is used to implement calculation variables, safety coefficient expression and fitness function design. The stability of the original slope-tunnel-bank slope under different conditions is calculated, after utilizing the secondary development function of the mathematical tool MATLAB for programming. We found that the bearing capacity of the original slopes is reduced as the tunnels are excavated and the safety coefficient is gradually decreased as loads of the embankment construction increased. After the embankment was constructed, the safety coefficient was 1.38, which is larger than the 1.3 value specified by China’s standards. Thus, the original slope-tunnel-bank slope would remain in a stable state.

Optimal Performance of a Nonlinear Gantry Crane System via Priority-based Fitness Scheme in Binary PSO Algorithm

International Nuclear Information System (INIS)

Jaafar, Hazriq Izzuan; Ali, Nursabillilah Mohd; Selamat, Nur Asmiza; Kassim, Anuar Mohamed; Mohamed, Z; Abidin, Amar Faiz Zainal; Jamian, J J

2013-01-01

This paper presents development of an optimal PID and PD controllers for controlling the nonlinear gantry crane system. The proposed Binary Particle Swarm Optimization (BPSO) algorithm that uses Priority-based Fitness Scheme is adopted in obtaining five optimal controller gains. The optimal gains are tested on a control structure that combines PID and PD controllers to examine system responses including trolley displacement and payload oscillation. The dynamic model of gantry crane system is derived using Lagrange equation. Simulation is conducted within Matlab environment to verify the performance of system in terms of settling time (Ts), steady state error (SSE) and overshoot (OS). This proposed technique demonstrates that implementation of Priority-based Fitness Scheme in BPSO is effective and able to move the trolley as fast as possible to the various desired position

Effective approach to spectroscopy and spectral analysis techniques using Matlab

Science.gov (United States)

Li, Xiang; Lv, Yong

2017-08-01

With the development of electronic information, computer and network, modern education technology has entered new era, which would give a great impact on teaching process. Spectroscopy and spectral analysis is an elective course for Optoelectronic Information Science and engineering. The teaching objective of this course is to master the basic concepts and principles of spectroscopy, spectral analysis and testing of basic technical means. Then, let the students learn the principle and technology of the spectrum to study the structure and state of the material and the developing process of the technology. MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, Based on the teaching practice, this paper summarizes the new situation of applying Matlab to the teaching of spectroscopy. This would be suitable for most of the current school multimedia assisted teaching

MatLab Programming for Engineers Having No Formal Programming Knowledge

Science.gov (United States)

Shaykhian, Linda H.; Shaykhian, Gholam Ali

2007-01-01

MatLab is one of the most widely used very high level programming languages for Scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. Also, stated are the current limitations of the MatLab, which possibly can be taken care of by Mathworks Inc. in a future version to make MatLab more versatile.

Cosmology with MATLAB

CERN Document Server

Green, Dan

2016-01-01

This volume makes explicit use of the synergy between cosmology and high energy physics, for example, supersymmetry and dark matter, or nucleosynthesis and the baryon-to-photon ratio. In particular the exciting possible connection between the recently discovered Higgs scalar and the scalar field responsible for inflation is explored.The recent great advances in the accuracy of the basic cosmological parameters is exploited in that no free scale parameters such as h appear, rather the basic calculations are done numerically using all sources of energy density simultaneously. Scripts are provided that allow the reader to calculate exact results for the basic parameters. Throughout MATLAB tools such as symbolic math, numerical solutions, plots and 'movies' of the dynamical evolution of systems are used. The GUI package is also shown as an example of the real time manipulation of parameters which is available to the reader.All the MATLAB scripts are made available to the reader to explore examples of the uses of ...

MatLab 1b

DEFF Research Database (Denmark)

Kristiansen, Heidi; Kaas, Thomas; Freil, Ole

Bogen indeholder fire kapitler: ’Tal i spil’, ’Spejlinger og mønstre’, ’Mønstre med farver, figurer og tal’ og ’Længde og vægt’. MATLAB: •bygger på en undersøgende og problemorienteret tilgang til matematikken •understøtter læringsmålstyret undervisning •har fokus på faglige samtaler og undersøge......Bogen indeholder fire kapitler: ’Tal i spil’, ’Spejlinger og mønstre’, ’Mønstre med farver, figurer og tal’ og ’Længde og vægt’. MATLAB: •bygger på en undersøgende og problemorienteret tilgang til matematikken •understøtter læringsmålstyret undervisning •har fokus på faglige samtaler og...

Parallel Sequential Monte Carlo for Efficient Density Combination: The Deco Matlab Toolbox

DEFF Research Database (Denmark)

Casarin, Roberto; Grassi, Stefano; Ravazzolo, Francesco

This paper presents the Matlab package DeCo (Density Combination) which is based on the paper by Billio et al. (2013) where a constructive Bayesian approach is presented for combining predictive densities originating from different models or other sources of information. The combination weights...... for standard CPU computing and for Graphical Process Unit (GPU) parallel computing. For the GPU implementation we use the Matlab parallel computing toolbox and show how to use General Purposes GPU computing almost effortless. This GPU implementation comes with a speed up of the execution time up to seventy...... times compared to a standard CPU Matlab implementation on a multicore CPU. We show the use of the package and the computational gain of the GPU version, through some simulation experiments and empirical applications....

Orthogonal transformations for change detection, Matlab code

DEFF Research Database (Denmark)

2005-01-01

Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data.......Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data....

Lightweight robotic mobility: template-based modeling for dynamics and controls using ADAMS/car and MATLAB

Science.gov (United States)

Adamczyk, Peter G.; Gorsich, David J.; Hudas, Greg R.; Overholt, James

2003-09-01

The U.S. Army is seeking to develop autonomous off-road mobile robots to perform tasks in the field such as supply delivery and reconnaissance in dangerous territory. A key problem to be solved with these robots is off-road mobility, to ensure that the robots can accomplish their tasks without loss or damage. We have developed a computer model of one such concept robot, the small-scale "T-1" omnidirectional vehicle (ODV), to study the effects of different control strategies on the robot's mobility in off-road settings. We built the dynamic model in ADAMS/Car and the control system in Matlab/Simulink. This paper presents the template-based method used to construct the ADAMS model of the T-1 ODV. It discusses the strengths and weaknesses of ADAMS/Car software in such an application, and describes the benefits and challenges of the approach as a whole. The paper also addresses effective linking of ADAMS/Car and Matlab for complete control system development. Finally, this paper includes a section describing the extension of the T-1 templates to other similar ODV concepts for rapid development.

Mathematical Modeling Using MATLAB

National Research Council Canada - National Science Library

Phillips, Donovan

1998-01-01

.... Mathematical Modeling Using MA MATLAB acts as a companion resource to A First Course in Mathematical Modeling with the goal of guiding the reader to a fuller understanding of the modeling process...

INTEGRACIÓN DE COMPONENTES COM DE MATLAB/SIMULINK EN EL ENTORNO CASE XBDK, PARA EL MODELADO DE SISTEMAS DE CONFORMACIÓN DE HAZ MATLAB/SIMULINK COM COMPONENT INTEGRATION FOR XBDK CASE ENVIRONMENT, ORIENTED TO BEAMFORMING APLICATIONS

Directory of Open Access Journals (Sweden)

Mariano Raboso Mateos

2009-04-01

Full Text Available En este artículo se describe la interfaz de acceso a Matlab desde la plataforma XBDK (XML-Based Beamforming Development Kit. La contribución más novedosa es la utilización del lenguaje de script Tcl/Tk para el acceso al entorno Matlab utilizando las interfaces COM, ofrecidas por el servicio Matlab Automation Server. La utilización de lenguajes de script tiene innumerables ventajas a la hora de diseñar, construir y depurar prototipos o automatizar procesos. Muchas de las herramientas que se utilizan hoy en día para procesado de señal de una u otra manera permiten la utilización de lenguajes de script. La combinación de un lenguaje de script, con la posibilidad de acceder de forma detallada a los servicios de Matlab, proporciona una manera flexible, rápida y potente, de integrar servicios en una herramienta CASE integrada como XBDK.This paper describes Matlab access within the XBDK (XML-Based Beamforming Development Kit platform. A well-known script language named Tcl/Tk has been used to perform Matlab COM interfacing, a powerful and little known mechanism, provided by Matlab Automation Server. Automation processing or prototype development, take advantage from script languages such Tcl/Tk. Most recent digital signal processing tools, provide mechanisms to be invoked by script languages. A language script plus COM integration, performs a detail, flexible, quick and powerful mechanism to provide services for a CASE integrated development environment such XBDK.

Design and Implementation of PV based Energy Harvester for WSN Node with MAIC algorithm

Directory of Open Access Journals (Sweden)

RAJENDRAN, H.

2015-05-01

Full Text Available Wireless sensor networks (WSNs are hardly in need of an additional source of power other than the normally used batteries, to increase the lifetime considerably. In this paper, mathematical modeling of photovoltaic energy harvesting (PVEH system for the WSN is presented. The system comprises of the solar PV panel, boost converter as maximum power point tracker with moving averaged incremental conductance (MAIC maximum power point (MPP algorithm, Ni-MH battery for energy storage, compensator, buck regulator and the mathematically modeled WSN mote. MAIC algorithm is proposed to avoid the effect of drastic variations in input irradiance, in locking the MPP point. WSN mote is modeled in both active and sleep state based on the power consumption. To maintain the voltage stability, proper compensator has been designed for the proposed system. The performance of the system is tested for dynamic variations of environmental conditions using MATLAB simulation. The proposed system has 50 to 60 percent improved conversion efficiency when compared to the conventional direct coupling method. The parameters of the photovoltaic panel model have been validated through experimentation. Also the practical verification of the operation of MPPT circuit has been performed.

Mobile Carbon Monoxide Monitoring System Based on Arduino-Matlab for Environmental Monitoring Application

Science.gov (United States)

Azieda Mohd Bakri, Nur; Junid, Syed Abdul Mutalib Al; Razak, Abdul Hadi Abdul; Idros, Mohd Faizul Md; Karimi Halim, Abdul

2015-11-01

Nowadays, the increasing level of carbon monoxide globally has become a serious environmental issue which has been highlighted in most of the country globally. The monitoring of carbon monoxide content is one of the approaches to identify the level of carbon monoxide pollution towards providing the solution for control the level of carbon monoxide produced. Thus, this paper proposed a mobile carbon monoxide monitoring system for measuring the carbon monoxide content based on Arduino-Matlab General User Interface (GUI). The objective of this project is to design, develop and implement the real-time mobile carbon monoxide sensor system and interfacing for measuring the level of carbon monoxide contamination in real environment. Four phases or stages of work have been carried out for the accomplishment of the project, which classified as sensor development, controlling and integrating sensor, data collection and data analysis. As a result, a complete design and developed system has been verified with the handheld industrial standard carbon monoxide sensor for calibrating the sensor sensitivity and measurement in the laboratory. Moreover, the system has been tested in real environments by measuring the level of carbon monoxide in three different lands used location; industrial area; residential area and main road (commercial area). In this real environment test, the industrial area recorded the highest reading with 71.23 ppm and 82.59 ppm for sensor 1 and sensor 2 respectively. As a conclusion, the mobile realtime carbon monoxide system based on the Arduino-Matlab is the best approach to measure the carbon monoxide concentration in different land-used since it does not require a manual data collection and reduce the complexity of the existing carbon monoxide level concentration measurement practise at the same time with a complete data analysis facilities.

Image based book cover recognition and retrieval

Science.gov (United States)

Sukhadan, Kalyani; Vijayarajan, V.; Krishnamoorthi, A.; Bessie Amali, D. Geraldine

2017-11-01

In this we are developing a graphical user interface using MATLAB for the users to check the information related to books in real time. We are taking the photos of the book cover using GUI, then by using MSER algorithm it will automatically detect all the features from the input image, after this it will filter bifurcate non-text features which will be based on morphological difference between text and non-text regions. We implemented a text character alignment algorithm which will improve the accuracy of the original text detection. We will also have a look upon the built in MATLAB OCR recognition algorithm and an open source OCR which is commonly used to perform better detection results, post detection algorithm is implemented and natural language processing to perform word correction and false detection inhibition. Finally, the detection result will be linked to internet to perform online matching. More than 86% accuracy can be obtained by this algorithm.

System design through Matlab, control toolbox and Simulink

CERN Document Server

Singh, Krishna K

2001-01-01

MATLAB , a software package developed by Math Works, Inc. is powerful, versatile and interactive software for scientific and technical computations including simulations. Specialised toolboxes provided with several built-in functions are a special feature of MATLAB . This book titled System Design through MATLAB , Control Toolbox and SIMULINK aims at getting the reader started with computations and simulations in system engineering quickly and easily and then proceeds to build concepts for advanced computations and simulations that includes the control and compensation of systems. Simulation through SIMULINK has also been described to allow the reader to get the feel of the real world situation. This book is appropriate for undergraduate students undergoing final semester of their project work, postgraduate students who have MATLAB integrated in their course or wish to take up simulation problem in the area of system engineering for their dissertation work and research scholars for whom MATLABÊ

Research on digital PID control algorithm for HPCT

International Nuclear Information System (INIS)

Zeng Yi; Li Rui; Shen Tianjian; Ke Xinhua

2009-01-01

Digital PID applied in high-precision HPCT (High-precision current transducer) based on Digital Signal Processor (DSP) TMS320F2812 and special D/A converter was researched. By using increment style PID Control algorithm, the stability and precision of high-precision HPCT output voltage is improved. On basis of deeply analysing incremental digital PID, the scheme model of HPCT is proposed, the feasibility simulation using Matlab is given. Practical hardware circuit verified the incremental PID has closed-loop control process in tracking HPCT output voltage. (authors)

ALGORITHMS AND PROGRAMS FOR STRONG GRAVITATIONAL LENSING IN KERR SPACE-TIME INCLUDING POLARIZATION

Energy Technology Data Exchange (ETDEWEB)

Chen, Bin; Maddumage, Prasad [Research Computing Center, Department of Scientific Computing, Florida State University, Tallahassee, FL 32306 (United States); Kantowski, Ronald; Dai, Xinyu; Baron, Eddie, E-mail: bchen3@fsu.edu [Homer L. Dodge Department of Physics and Astronomy, University of Oklahoma, Norman, OK 73019 (United States)

2015-05-15

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravity field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python.

ALGORITHMS AND PROGRAMS FOR STRONG GRAVITATIONAL LENSING IN KERR SPACE-TIME INCLUDING POLARIZATION

International Nuclear Information System (INIS)

Chen, Bin; Maddumage, Prasad; Kantowski, Ronald; Dai, Xinyu; Baron, Eddie

2015-01-01

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravity field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python

Sensitivity Analysis of a CPAM Inverse Algorithm for Composite Laminates Characterization

Directory of Open Access Journals (Sweden)

Farshid Masoumi

2017-01-01

Full Text Available Using experimental data and numerical simulations, a new combined technique is presented for characterization of thin and thick orthotropic composite laminates. Four or five elastic constants, as well as ply orientation angles, are considered as the unknown parameters. The material characterization is first examined for isotropic plates under different boundary conditions to evaluate the method’s accuracy. The proposed algorithm, so-called CPAM (Combined Programs of ABAQUS and MATLAB, utilizes an optimization procedure and makes simultaneous use of vibration test data together with their corresponding numerical solutions. The numerical solutions are based on a commercial finite element package for efficiently identifying the material properties. An inverse method based on particle swarm optimization algorithm is further provided using MATLAB software. The error function to be minimized is the sum of squared differences between experimental and simulated data of eigenfrequencies. To evaluate the robustness of the model’s results in the presence of uncertainty and unwanted noises, a sensitivity analysis that employs Gaussian disorder model is directly applied to the measured frequencies. The results with high accuracy confirm the validity and capability of the present method in simultaneous determination of mechanical constants and fiber orientation angles of composite laminates as compared to prior methods.

An Algorithm Approach for the Analysis of Urban Land-Use/Cover: Logic Filters

Directory of Open Access Journals (Sweden)

Şinasi Kaya

2014-11-01

Full Text Available Accurate classification of land-use/cover based on remotely sensed data is important for interpreters who analyze time or event-based change on certain areas. Any method that has user flexibility on area selection provides great simplicity during analysis, since the analyzer may need to work on a specific area of interest instead of dealing with the entire remotely sensed data. The objectives of the paper are to develop an automation algorithm using Matlab & Simulink on user selected areas, to filter V-I-S (Vegetation, Impervious, Soil components using the algorithm, to analyze the components according to upper and lower threshold values based on each band histogram, and finally to obtain land-use/cover map combining the V-I-S components. LANDSAT 5TM satellite data covering Istanbul and Izmit regions are utilized, and 4, 3, 2 (RGB band combination is selected to fulfill the aims of the study. These referred bands are normalized, and V-I-S components of each band are determined. This methodology that uses Matlab & Simulink program is equally successful like the unsupervised and supervised methods. Practices with these methods that lead to qualitative and quantitative assessments of selected urban areas will further provide important spatial information and data especially to the urban planners and decision-makers.

First experience with the MATLAB Middle Layer at ANKA

International Nuclear Information System (INIS)

Marsching, S.; Huttel, E.; Klein, M.; Mueller, A.S.; Smale, N.J.

2012-01-01

ANKA is a synchrotron radiation facility at the Karlsruhe Institute of Technology. The MATLAB Middle Layer (MML) is a collection of scripts for the MATLAB programming environment, designed to control and measure parameters of an accelerator. MML has been adapted for use at ANKA and the commissioning process was quite simple and would have been even simpler if we had used one of the control systems directly supported by MML. At ANKA MML is used for accelerator physics studies and regular tasks like beam-based alignment and response matrix analysis using LOCO. Furthermore, we intend to study the MML as default orbit correction tool for user operation. We report on the experience made during the commissioning process and present the latest results obtained while using the MML for machine studies. MML simplifies the task of performing a beam-based alignment dramatically compared to our old solution which required the user to copy the measured data into specific files for further evaluation

Novel medical image enhancement algorithms

Science.gov (United States)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Migration of a Real-Time Optimal-Control Algorithm: From MATLAB (Trademark) to Field Programmable Gate Array (FPGA)

National Research Council Canada - National Science Library

Moon, II, Ron L

2005-01-01

...) development environment into an FPGA-based embedded-platform development board. Research at the Naval Postgraduate School has produced a revolutionary time-optimal spacecraft control algorithm based upon the Legendre Pseudospectral method...

System Simulation of Nuclear Power Plant by Coupling RELAP5 and Matlab/Simulink

International Nuclear Information System (INIS)

Meng Lin; Dong Hou; Zhihong Xu; Yanhua Yang; Ronghua Zhang

2006-01-01

Since RELAP5 code has general and advanced features in thermal-hydraulic computation, it has been widely used in transient and accident safety analysis, experiment planning analysis, and system simulation, etc. So we wish to design, analyze, verify a new Instrumentation And Control (I and C) system of Nuclear Power Plant (NPP) based on the best-estimated code, and even develop our engineering simulator. But because of limited function of simulating control and protection system in RELAP5, it is necessary to expand the function for high efficient, accurate, flexible design and simulation of I and C system. Matlab/Simulink, a scientific computation software, just can compensate the limitation, which is a powerful tool in research and simulation of plant process control. The software is selected as I and C part to be coupled with RELAP5 code to realize system simulation of NPPs. There are two key techniques to be solved. One is the dynamic data exchange, by which Matlab/Simulink receives plant parameters and returns control results. Database is used to communicate the two codes. Accordingly, Dynamic Link Library (DLL) is applied to link database in RELAP5, while DLL and S-Function is applied in Matlab/Simulink. The other problem is synchronization between the two codes for ensuring consistency in global simulation time. Because Matlab/Simulink always computes faster than RELAP5, the simulation time is sent by RELAP5 and received by Matlab/Simulink. A time control subroutine is added into the simulation procedure of Matlab/Simulink to control its simulation advancement. Through these ways, Matlab/Simulink is dynamically coupled with RELAP5. Thus, in Matlab/Simulink, we can freely design control and protection logic of NPPs and test it with best-estimated plant model feedback. A test will be shown to illuminate that results of coupling calculation are nearly the same with one of single RELAP5 with control logic. In practice, a real Pressurized Water Reactor (PWR) is

An Improvement of a Fuzzy Logic-Controlled Maximum Power Point Tracking Algorithm for Photovoltic Applications

Directory of Open Access Journals (Sweden)

Woonki Na

2017-03-01

Full Text Available This paper presents an improved maximum power point tracking (MPPT algorithm using a fuzzy logic controller (FLC in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.

Vector Control Algorithm for Electric Vehicle AC Induction Motor Based on Improved Variable Gain PID Controller

Directory of Open Access Journals (Sweden)

Gang Qin

2015-01-01

Full Text Available The acceleration performance of EV, which affects a lot of performances of EV such as start-up, overtaking, driving safety, and ride comfort, has become increasingly popular in recent researches. An improved variable gain PID control algorithm to improve the acceleration performance is proposed in this paper. The results of simulation with Matlab/Simulink demonstrate the effectiveness of the proposed algorithm through the control performance of motor velocity, motor torque, and three-phase current of motor. Moreover, it is investigated that the proposed controller is valid by comparison with the other PID controllers. Furthermore, the AC induction motor experiment set is constructed to verify the effect of proposed controller.

Opposition-Based Adaptive Fireworks Algorithm

Directory of Open Access Journals (Sweden)

Chibing Gong

2016-07-01

Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.

Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

DEFF Research Database (Denmark)

Hansen, Per Christian; Jensen, Søren Holdt

2007-01-01

We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... with working Matlab code and applications in speech processing....

GRace: a MATLAB-based application for fitting the discrimination-association model.

Science.gov (United States)

Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

2014-10-28

The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

Opposition-Based Adaptive Fireworks Algorithm

OpenAIRE

Chibing Gong

2016-01-01

A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based a...

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

Science.gov (United States)

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Subband/Transform MATLAB Functions For Processing Images

Science.gov (United States)

Glover, D.

1995-01-01

SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

An Introduction to Transient Engine Applications Using the Numerical Propulsion System Simulation (NPSS) and MATLAB

Science.gov (United States)

Chin, Jeffrey C.; Csank, Jeffrey T.; Haller, William J.; Seidel, Jonathan A.

2016-01-01

This document outlines methodologies designed to improve the interface between the Numerical Propulsion System Simulation framework and various control and dynamic analyses developed in the Matlab and Simulink environment. Although NPSS is most commonly used for steady-state modeling, this paper is intended to supplement the relatively sparse documentation on it's transient analysis functionality. Matlab has become an extremely popular engineering environment, and better methodologies are necessary to develop tools that leverage the benefits of these disparate frameworks. Transient analysis is not a new feature of the Numerical Propulsion System Simulation (NPSS), but transient considerations are becoming more pertinent as multidisciplinary trade-offs begin to play a larger role in advanced engine designs. This paper serves to supplement the relatively sparse documentation on transient modeling and cover the budding convergence between NPSS and Matlab based modeling toolsets. The following sections explore various design patterns to rapidly develop transient models. Each approach starts with a base model built with NPSS, and assumes the reader already has a basic understanding of how to construct a steady-state model. The second half of the paper focuses on further enhancements required to subsequently interface NPSS with Matlab codes. The first method being the simplest and most straightforward but performance constrained, and the last being the most abstract. These methods aren't mutually exclusive and the specific implementation details could vary greatly based on the designer's discretion. Basic recommendations are provided to organize model logic in a format most easily amenable to integration with existing Matlab control toolsets.

Experiences with Matlab and VRML in Functional Neuroimaging Visualizations

DEFF Research Database (Denmark)

Nielsen, Finn Årup; Hansen, Lars Kai

2000-01-01

We describe some experiences with Matlab and VRML. We are developing a toolbox for neuroinformatics and describe some of the functionalities we have implemented or will implement and how Matlab and VRML support the implementation....

An Improved Perturb and Observe Algorithm for Photovoltaic Motion Carriers

Science.gov (United States)

Peng, Lele; Xu, Wei; Li, Liming; Zheng, Shubin

2018-03-01

An improved perturbation and observation algorithm for photovoltaic motion carriers is proposed in this paper. The model of the proposed algorithm is given by using Lambert W function and tangent error method. Moreover, by using matlab and experiment of photovoltaic system, the tracking performance of the proposed algorithm is tested. And the results demonstrate that the improved algorithm has fast tracking speed and high efficiency. Furthermore, the energy conversion efficiency by the improved method has increased by nearly 8.2%.

A matlab framework for estimation of NLME models using stochastic differential equations: applications for estimation of insulin secretion rates.

Science.gov (United States)

Mortensen, Stig B; Klim, Søren; Dammann, Bernd; Kristensen, Niels R; Madsen, Henrik; Overgaard, Rune V

2007-10-01

The non-linear mixed-effects model based on stochastic differential equations (SDEs) provides an attractive residual error model, that is able to handle serially correlated residuals typically arising from structural mis-specification of the true underlying model. The use of SDEs also opens up for new tools for model development and easily allows for tracking of unknown inputs and parameters over time. An algorithm for maximum likelihood estimation of the model has earlier been proposed, and the present paper presents the first general implementation of this algorithm. The implementation is done in Matlab and also demonstrates the use of parallel computing for improved estimation times. The use of the implementation is illustrated by two examples of application which focus on the ability of the model to estimate unknown inputs facilitated by the extension to SDEs. The first application is a deconvolution-type estimation of the insulin secretion rate based on a linear two-compartment model for C-peptide measurements. In the second application the model is extended to also give an estimate of the time varying liver extraction based on both C-peptide and insulin measurements.

Multi-objective thermodynamic optimization of an irreversible regenerative Brayton cycle using evolutionary algorithm and decision making

OpenAIRE

Rajesh Kumar; S.C. Kaushik; Raj Kumar; Ranjana Hans

2016-01-01

Brayton heat engine model is developed in MATLAB simulink environment and thermodynamic optimization based on finite time thermodynamic analysis along with multiple criteria is implemented. The proposed work investigates optimal values of various decision variables that simultaneously optimize power output, thermal efficiency and ecological function using evolutionary algorithm based on NSGA-II. Pareto optimal frontier between triple and dual objectives is obtained and best optimal value is s...

An integrated environment for fast development and performance assessment of sonar image processing algorithms - SSIE

DEFF Research Database (Denmark)

Henriksen, Lars

1996-01-01

The sonar simulator integrated environment (SSIE) is a tool for developing high performance processing algorithms for single or sequences of sonar images. The tool is based on MATLAB providing a very short lead time from concept to executable code and thereby assessment of the algorithms tested...... of the algorithms is the availability of sonar images. To accommodate this problem the SSIE has been equipped with a simulator capable of generating high fidelity sonar images for a given scene of objects, sea-bed AUV path, etc. In the paper the main components of the SSIE is described and examples of different...... processing steps are given...

PFA toolbox: a MATLAB tool for Metabolic Flux Analysis.

Science.gov (United States)

Morales, Yeimy; Bosque, Gabriel; Vehí, Josep; Picó, Jesús; Llaneras, Francisco

2016-07-11

Metabolic Flux Analysis (MFA) is a methodology that has been successfully applied to estimate metabolic fluxes in living cells. However, traditional frameworks based on this approach have some limitations, particularly when measurements are scarce and imprecise. This is very common in industrial environments. The PFA Toolbox can be used to face those scenarios. Here we present the PFA (Possibilistic Flux Analysis) Toolbox for MATLAB, which simplifies the use of Interval and Possibilistic Metabolic Flux Analysis. The main features of the PFA Toolbox are the following: (a) It provides reliable MFA estimations in scenarios where only a few fluxes can be measured or those available are imprecise. (b) It provides tools to easily plot the results as interval estimates or flux distributions. (c) It is composed of simple functions that MATLAB users can apply in flexible ways. (d) It includes a Graphical User Interface (GUI), which provides a visual representation of the measurements and their uncertainty. (e) It can use stoichiometric models in COBRA format. In addition, the PFA Toolbox includes a User's Guide with a thorough description of its functions and several examples. The PFA Toolbox for MATLAB is a freely available Toolbox that is able to perform Interval and Possibilistic MFA estimations.

ANNIT - An Efficient Inversion Algorithm based on Prediction Principles

Science.gov (United States)

Růžek, B.; Kolář, P.

2009-04-01

Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good

Dynamic route guidance algorithm based algorithm based on artificial immune system

Institute of Scientific and Technical Information of China (English)

无

2007-01-01

To improve the performance of the K-shortest paths search in intelligent traffic guidance systems,this paper proposes an optimal search algorithm based on the intelligent optimization search theory and the memphor mechanism of vertebrate immune systems.This algorithm,applied to the urban traffic network model established by the node-expanding method,can expediently realize K-shortest paths search in the urban traffic guidance systems.Because of the immune memory and global parallel search ability from artificial immune systems,K shortest paths can be found without any repeat,which indicates evidently the superiority of the algorithm to the conventional ones.Not only does it perform a better parallelism,the algorithm also prevents premature phenomenon that often occurs in genetic algorithms.Thus,it is especially suitable for real-time requirement of the traffic guidance system and other engineering optimal applications.A case study verifies the efficiency and the practicability of the algorithm aforementioned.

Introduction to finite element analysis using MATLAB and Abaqus

CERN Document Server

Khennane, Amar

2013-01-01

There are some books that target the theory of the finite element, while others focus on the programming side of things. Introduction to Finite Element Analysis Using MATLAB(R) and Abaqus accomplishes both. This book teaches the first principles of the finite element method. It presents the theory of the finite element method while maintaining a balance between its mathematical formulation, programming implementation, and application using commercial software. The computer implementation is carried out using MATLAB, while the practical applications are carried out in both MATLAB and Abaqus. MA

Digital signal processing using MATLAB

CERN Document Server

Schilling, Robert L

2016-01-01

Focus on the development, implementation, and application of modern DSP techniques with DIGITAL SIGNAL PROCESSING USING MATLAB(R), 3E. Written in an engaging, informal style, this edition immediately captures your attention and encourages you to explore each critical topic. Every chapter starts with a motivational section that highlights practical examples and challenges that you can solve using techniques covered in the chapter. Each chapter concludes with a detailed case study example, a chapter summary with learning outcomes, and practical homework problems cross-referenced to specific chapter sections for your convenience. DSP Companion software accompanies each book to enable further investigation. The DSP Companion software operates with MATLAB(R) and provides intriguing demonstrations as well as interactive explorations of analysis and design concepts.

POWER ELECTRONIC SYSTEM FOR POWER ELECTRIC VEHICLES WITH ALGORITHMS OF SYNCHRONOUS MODULATION

OpenAIRE

Oleschuk V.; Ermuratskii V.

2014-01-01

Schemes of synchronous space-vector modulation have been adapted for control of split-phase drive for electric vehicle with open-end windings of induction motor, supplied by several voltage source inverters. MATLAB-based simulation of processes in this system has been executed. It has been shown, that the use of algorithms of synchronous modulation provides symmetry of phase voltage waveforms for any ratio between the switching frequency and fundamental frequency, and for any voltage magnitud...

Application of integral-separated PID algorithm in orbit feedback

International Nuclear Information System (INIS)

Xuan, K.; Bao, X.; Li, C.; Li, W.; Liu, G.; Wang, J.; Wang, L.

2012-01-01

The algorithm in the feedback system has important influence on the performance of the beam orbit. PID (Proportion Integration Differentiation) algorithm is widely used in the beam orbit feedback system; however, the deficiency of PID algorithm is a big overshooting in strong perturbations. In order to overcome the deficiencies, the integral-separated PID algorithm is developed. When the closed orbit distortion is too large, it cancels integration action until the closed orbit distortion is lower than the separation threshold value. The implementation of integral-separated PID algorithm with MATLAB is described in this paper. The simulation results show that this algorithm can improve the control precision. (authors)

Digital signal processing for wireless communication using Matlab

CERN Document Server

Gopi, E S

2016-01-01

This book examines signal processing techniques used in wireless communication illustrated by using the Matlab program. The author discusses these techniques as they relate to Doppler spread; delay spread; Rayleigh and Rician channel modeling; rake receiver; diversity techniques; MIMO and OFDM -based transmission techniques; and array signal processing. Related topics such as detection theory, link budget, multiple access techniques, and spread spectrum are also covered.   ·         Illustrates signal processing techniques involved in wireless communication using Matlab ·         Discusses multiple access techniques such as Frequency division multiple access, Time division multiple access, and Code division multiple access ·         Covers band pass modulation techniques such as Binary phase shift keying, Differential phase shift keying, Quadrature phase shift keying, Binary frequency shift keying, Minimum shift keying, and Gaussian minimum shift keying.

Algorithm for Fast and Efficient Detection and Reaction to Angle Instability Conditions Using Phasor Measurement Unit Data

Directory of Open Access Journals (Sweden)

Igor Ivanković

2018-03-01

Full Text Available In wide area monitoring, protection, and control (WAMPAC systems, angle stability of transmission network is monitored using data from phasor measurement units (PMU placed on transmission lines. Based on this PMU data stream advanced algorithm for out-of-step condition detection and early warning issuing is developed. The algorithm based on theoretical background described in this paper is backed up by the data and results from corresponding simulations done in Matlab environment. Presented results aim to provide the insights of the potential benefits, such as fast and efficient detection and reaction to angle instability, this algorithm can have on the improvement of the power system protection. Accordingly, suggestion is given how the developed algorithm can be implemented in protection segments of the WAMPAC systems in the transmission system operator control centers.

Archimedean copula estimation of distribution algorithm based on artificial bee colony algorithm

Institute of Scientific and Technical Information of China (English)

Haidong Xu; Mingyan Jiang; Kun Xu

2015-01-01

The artificial bee colony (ABC) algorithm is a com-petitive stochastic population-based optimization algorithm. How-ever, the ABC algorithm does not use the social information and lacks the knowledge of the problem structure, which leads to in-sufficiency in both convergent speed and searching precision. Archimedean copula estimation of distribution algorithm (ACEDA) is a relatively simple, time-economic and multivariate correlated EDA. This paper proposes a novel hybrid algorithm based on the ABC algorithm and ACEDA cal ed Archimedean copula estima-tion of distribution based on the artificial bee colony (ACABC) algorithm. The hybrid algorithm utilizes ACEDA to estimate the distribution model and then uses the information to help artificial bees to search more efficiently in the search space. Six bench-mark functions are introduced to assess the performance of the ACABC algorithm on numerical function optimization. Experimen-tal results show that the ACABC algorithm converges much faster with greater precision compared with the ABC algorithm, ACEDA and the global best (gbest)-guided ABC (GABC) algorithm in most of the experiments.

Stabilization of Electromagnetic Suspension System Behavior by Genetic Algorithm

Directory of Open Access Journals (Sweden)

Abbas Najar Khoda Bakhsh

2012-07-01

Full Text Available Electromagnetic suspension system with a nonlinear and unstable behavior, is used in maglev trains. In this paper a linear mathematical model of system is achieved and the state feedback method is used to improve the system stability. The control coefficients are tuned by two different methods, Riccati and a new method based on Genetic algorithm. In this new proposed method, we use Genetic algorithm to achieve the optimum values of control coefficients. The results of the system simulation by Matlab indicate the effectiveness of new proposed system. When a new reference of air gap is needed or a new external force is added, the proposed system could omit the vibration and shake of the train coupe and so, passengers feel more comfortable.

Regularization Tools Version 3.0 for Matlab 5.2

DEFF Research Database (Denmark)

Hansen, Per Christian

1999-01-01

This communication describes Version 3.0 of Regularization Tools, a Matlab package for analysis and solution of discrete ill-posed problems.......This communication describes Version 3.0 of Regularization Tools, a Matlab package for analysis and solution of discrete ill-posed problems....

Research Reactor Power Control System Design by MATLAB/SIMULINK

International Nuclear Information System (INIS)

Baang, Dane; Suh, Yong Suk; Kim, Young Ki; Im, Ki Hong

2013-01-01

In this study it is presented that MATLAB/SIMULINK can be efficiently used for modeling and power control system design for research reactors. The presented power control system deals with various functions including reactivity control, signals processing, reactivity calculation, alarm request generation, etc., thus it is required to test all the software logic using proper model for reactor, control rods, and field instruments. In MATLAB/SIMULINK tool, point kinetics, thermal model, control absorber rod model, and other instrument models were developed based on reactor parameters and known properties of each component or system. The software for power control system was invented and linked to the model to test each function. From the simulation result it is shown that the power control performance and other functions of the system can be easily tested and analyzed in the proposed simulation structure

Novel control algorithm of braking energy regeneration system for an electric vehicle during safety–critical driving maneuvers

International Nuclear Information System (INIS)

Lv, Chen; Zhang, Junzhi; Li, Yutong; Yuan, Ye

2015-01-01

Highlights: • Models of an electric vehicle with regenerative braking system (RBS) are built. • Control algorithm of RBS under safety–critical driving maneuvers is proposed. • Simulations and HIL tests of the proposed strategy are conducted. • Performance improvement of vehicle’s mean deceleration is up to 13.89%. • Test results verify the feasibility and effectiveness of the proposed method. - Abstract: This paper mainly focuses on control algorithm of the braking energy regeneration system of an electric bus under safety–critical driving situations. With the aims of guaranteeing vehicle stability in various types of tyre–road adhesion conditions, based on the characteristics of electrified powertrain, a novel control algorithm of regenerative braking system is proposed for electric vehicles during anti-lock braking procedures. First, the models of vehicle dynamics and main components including braking energy regenerative system of the case-study electric bus are built in MATLAB/Simulink. Then, based on the phase-plane method, the optimal brake torque is calculated for ABS control of vehicle. Next, a novel allocation strategy, wherein the target optimal brake torque is divided into two parts that are handled separately by the regenerative and friction brakes, is developed. Simulations of the proposed control strategy are conducted based on system models built using MATLAB/Simulink. The simulation results demonstrate that the developed strategy enables improved control in terms of vehicle stability and braking performance under different emergency driving conditions. To further verify the synthesized control algorithm, hardware-in-the-loop tests are also performed. The experimental results validate the simulation data and verify the feasibility and effectiveness of the developed control algorithm.

The finite volume method in computational fluid dynamics an advanced introduction with OpenFOAM and Matlab

CERN Document Server

Moukalled, F; Darwish, M

2016-01-01

This textbook explores both the theoretical foundation of the Finite Volume Method (FVM) and its applications in Computational Fluid Dynamics (CFD). Readers will discover a thorough explanation of the FVM numerics and algorithms used for the simulation of incompressible and compressible fluid flows, along with a detailed examination of the components needed for the development of a collocated unstructured pressure-based CFD solver. Two particular CFD codes are explored. The first is uFVM, a three-dimensional unstructured pressure-based finite volume academic CFD code, implemented within Matlab. The second is OpenFOAM®, an open source framework used in the development of a range of CFD programs for the simulation of industrial scale flow problems. With over 220 figures, numerous examples and more than one hundred exercise on FVM numerics, programming, and applications, this textbook is suitable for use in an introductory course on the FVM, in an advanced course on numerics, and as a reference for CFD programm...

Fitting model-based psychometric functions to simultaneity and temporal-order judgment data: MATLAB and R routines.

Science.gov (United States)

Alcalá-Quintana, Rocío; García-Pérez, Miguel A

2013-12-01

Research on temporal-order perception uses temporal-order judgment (TOJ) tasks or synchrony judgment (SJ) tasks in their binary SJ2 or ternary SJ3 variants. In all cases, two stimuli are presented with some temporal delay, and observers judge the order of presentation. Arbitrary psychometric functions are typically fitted to obtain performance measures such as sensitivity or the point of subjective simultaneity, but the parameters of these functions are uninterpretable. We describe routines in MATLAB and R that fit model-based functions whose parameters are interpretable in terms of the processes underlying temporal-order and simultaneity judgments and responses. These functions arise from an independent-channels model assuming arrival latencies with exponential distributions and a trichotomous decision space. Different routines fit data separately for SJ2, SJ3, and TOJ tasks, jointly for any two tasks, or also jointly for the three tasks (for common cases in which two or even the three tasks were used with the same stimuli and participants). Additional routines provide bootstrap p-values and confidence intervals for estimated parameters. A further routine is included that obtains performance measures from the fitted functions. An R package for Windows and source code of the MATLAB and R routines are available as Supplementary Files.

Study on the effects of sample selection on spectral reflectance reconstruction based on the algorithm of compressive sensing

International Nuclear Information System (INIS)

Zhang, Leihong; Liang, Dong

2016-01-01

In order to solve the problem that reconstruction efficiency and precision is not high, in this paper different samples are selected to reconstruct spectral reflectance, and a new kind of spectral reflectance reconstruction method based on the algorithm of compressive sensing is provided. Four different color numbers of matte color cards such as the ColorChecker Color Rendition Chart and Color Checker SG, the copperplate paper spot color card of Panton, and the Munsell colors card are chosen as training samples, the spectral image is reconstructed respectively by the algorithm of compressive sensing and pseudo-inverse and Wiener, and the results are compared. These methods of spectral reconstruction are evaluated by root mean square error and color difference accuracy. The experiments show that the cumulative contribution rate and color difference of the Munsell colors card are better than those of the other three numbers of color cards in the same conditions of reconstruction, and the accuracy of the spectral reconstruction will be affected by the training sample of different numbers of color cards. The key technology of reconstruction means that the uniformity and representation of the training sample selection has important significance upon reconstruction. In this paper, the influence of the sample selection on the spectral image reconstruction is studied. The precision of the spectral reconstruction based on the algorithm of compressive sensing is higher than that of the traditional algorithm of spectral reconstruction. By the MATLAB simulation results, it can be seen that the spectral reconstruction precision and efficiency are affected by the different color numbers of the training sample. (paper)

Neurient: An Algorithm for Automatic Tracing of Confluent Neuronal Images to Determine Alignment

Science.gov (United States)

Mitchel, J.A.; Martin, I.S.

2013-01-01

A goal of neural tissue engineering is the development and evaluation of materials that guide neuronal growth and alignment. However, the methods available to quantitatively evaluate the response of neurons to guidance materials are limited and/or expensive, and may require manual tracing to be performed by the researcher. We have developed an open source, automated Matlab-based algorithm, building on previously published methods, to trace and quantify alignment of fluorescent images of neurons in culture. The algorithm is divided into three phases, including computation of a lookup table which contains directional information for each image, location of a set of seed points which may lie along neurite centerlines, and tracing neurites starting with each seed point and indexing into the lookup table. This method was used to obtain quantitative alignment data for complex images of densely cultured neurons. Complete automation of tracing allows for unsupervised processing of large numbers of images. Following image processing with our algorithm, available metrics to quantify neurite alignment include angular histograms, percent of neurite segments in a given direction, and mean neurite angle. The alignment information obtained from traced images can be used to compare the response of neurons to a range of conditions. This tracing algorithm is freely available to the scientific community under the name Neurient, and its implementation in Matlab allows a wide range of researchers to use a standardized, open source method to quantitatively evaluate the alignment of dense neuronal cultures. PMID:23384629

MATLAB as an incentive for student learning of skills

Science.gov (United States)

Bank, C. G.; Ghent, R. R.

2016-12-01

Our course "Computational Geology" takes a holistic approach to student learning by using MATLAB as a focal point to increase students' computing, quantitative reasoning, data analysis, report writing, and teamwork skills. The course, taught since 2007 with recent enrollments around 35 and aimed at 2nd to 3rd-year students, is required for the Geology and Earth and Environmental Systems major programs, and can be chosen as elective in our other programs, including Geophysics. The course is divided into five projects: Pacific plate velocity from the Hawaiian hotspot track, predicting CO2 concentration in the atmosphere, volume of Earth's oceans and sea-level rise, comparing wind directions for Vancouver and Squamish, and groundwater flow. Each project is based on real data, focusses on a mathematical concept (linear interpolation, gradients, descriptive statistics, differential equations) and highlights a programming task (arrays, functions, text file input/output, curve fitting). Working in teams of three, students need to develop a conceptional model to explain the data, and write MATLAB code to visualize the data and match it to their conceptional model. The programming is guided, and students work individually on different aspects (for example: reading the data, fitting a function, unit conversion) which they need to put together to solve the problem. They then synthesize their thought process in a paper. Anecdotal evidence shows that students continue using MATLAB in other courses.

Mathematical algorithm development and parametric studies with the GEOFRAC three-dimensional stochastic model of natural rock fracture systems

Science.gov (United States)

Ivanova, Violeta M.; Sousa, Rita; Murrihy, Brian; Einstein, Herbert H.

2014-06-01

This paper presents results from research conducted at MIT during 2010-2012 on modeling of natural rock fracture systems with the GEOFRAC three-dimensional stochastic model. Following a background summary of discrete fracture network models and a brief introduction of GEOFRAC, the paper provides a thorough description of the newly developed mathematical and computer algorithms for fracture intensity, aperture, and intersection representation, which have been implemented in MATLAB. The new methods optimize, in particular, the representation of fracture intensity in terms of cumulative fracture area per unit volume, P32, via the Poisson-Voronoi Tessellation of planes into polygonal fracture shapes. In addition, fracture apertures now can be represented probabilistically or deterministically whereas the newly implemented intersection algorithms allow for computing discrete pathways of interconnected fractures. In conclusion, results from a statistical parametric study, which was conducted with the enhanced GEOFRAC model and the new MATLAB-based Monte Carlo simulation program FRACSIM, demonstrate how fracture intensity, size, and orientations influence fracture connectivity.

Algorithms evaluation for transformers differential protection; Avaliacao de algoritmos para protecao diferencial de transformadores

Energy Technology Data Exchange (ETDEWEB)

Piovesan, Luis Sergio

1997-07-01

The appliance of two algorithms is evaluated, one based in Fourier analysis and other based in a rectangular transform technique over Fourier analysis, to be used in digital logical circuits (digital protection relays) for the purpose of differential protection of power transformers (ANSI 87T). The first chapter has a brief introduction about electrical protection. The second chapter discusses the general problems of transform protection, the development of digital technology and, with more detail, the differential protection associated to this technology. In this chapter are presented the particular aspects of transformers differential protection concerning sensibility, inrush current situations and harmonic distortions caused by transformer core saturations and the differential protection algorithms and their applications in a specific relay design. In chapter three, a method to make possible testing the protection performance is developed. This work applies digital simulations using EMTP to generate current signal of transformer operation and fault conditions. Digital simulation using Matlab is used to simulate the protection. The EMTP generated field signals are sent to the relay under test, furnishing data of normal operation, internal and external faults. The relay logic simulator at Matlab will work this data and so, it will be possible to verify and evaluate the algorithm behavior and performance. Chapter 4 shows the protection operation over simulations of several of transformer operation and fault conditions. The last chapter presents a conclusion about the protection performance, discussions about all the methods applied in this work and suggestions for further studies. (author)

Energy efficient model based algorithm for control of building HVAC systems.

Science.gov (United States)

Kirubakaran, V; Sahu, Chinmay; Radhakrishnan, T K; Sivakumaran, N

2015-11-01

Energy efficient designs are receiving increasing attention in various fields of engineering. Heating ventilation and air conditioning (HVAC) control system designs involve improved energy usage with an acceptable relaxation in thermal comfort. In this paper, real time data from a building HVAC system provided by BuildingLAB is considered. A resistor-capacitor (RC) framework for representing thermal dynamics of the building is estimated using particle swarm optimization (PSO) algorithm. With objective costs as thermal comfort (deviation of room temperature from required temperature) and energy measure (Ecm) explicit MPC design for this building model is executed based on its state space representation of the supply water temperature (input)/room temperature (output) dynamics. The controllers are subjected to servo tracking and external disturbance (ambient temperature) is provided from the real time data during closed loop control. The control strategies are ported on a PIC32mx series microcontroller platform. The building model is implemented in MATLAB and hardware in loop (HIL) testing of the strategies is executed over a USB port. Results indicate that compared to traditional proportional integral (PI) controllers, the explicit MPC's improve both energy efficiency and thermal comfort significantly. Copyright © 2015 Elsevier Inc. All rights reserved.

Modelling and Simulation Based on Matlab/Simulink: A Press Mechanism

International Nuclear Information System (INIS)

Halicioglu, R; Dulger, L C; Bozdana, A T

2014-01-01

In this study, design and kinematic analysis of a crank-slider mechanism for a crank press is studied. The crank-slider mechanism is the commonly applied one as direct and indirect drive alternatives in practice. Since inexpensiveness, flexibility and controllability are getting more and more important in many industrial applications especially in automotive industry, a crank press with servo actuator (servo crank press) is taken as an application. Design and kinematic analysis of representative mechanism is presented with geometrical analysis for the inverse kinematic of the mechanism by using desired motion concept of slider. The mechanism is modelled in MATLAB/Simulink platform. The simulation results are presented herein

Modelling and Simulation Based on Matlab/Simulink: A Press Mechanism

Science.gov (United States)

Halicioglu, R.; Dulger, L. C.; Bozdana, A. T.

2014-03-01

In this study, design and kinematic analysis of a crank-slider mechanism for a crank press is studied. The crank-slider mechanism is the commonly applied one as direct and indirect drive alternatives in practice. Since inexpensiveness, flexibility and controllability are getting more and more important in many industrial applications especially in automotive industry, a crank press with servo actuator (servo crank press) is taken as an application. Design and kinematic analysis of representative mechanism is presented with geometrical analysis for the inverse kinematic of the mechanism by using desired motion concept of slider. The mechanism is modelled in MATLAB/Simulink platform. The simulation results are presented herein.

A Graphical User Interface to Generalized Linear Models in MATLAB

Directory of Open Access Journals (Sweden)

Peter Dunn

1999-07-01

Full Text Available Generalized linear models unite a wide variety of statistical models in a common theoretical framework. This paper discusses GLMLAB-software that enables such models to be fitted in the popular mathematical package MATLAB. It provides a graphical user interface to the powerful MATLAB computational engine to produce a program that is easy to use but with many features, including offsets, prior weights and user-defined distributions and link functions. MATLAB's graphical capacities are also utilized in providing a number of simple residual diagnostic plots.

Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

Directory of Open Access Journals (Sweden)

Fernando A. Auat Cheein

2013-01-01

Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

Training course "Porting code from Matlab to Python"

OpenAIRE

Diaz, Sandra; Klijn, Wouter; Deepu, Rajalekshmi; Peyser, Alexander; Oden, Lena

2017-01-01

Python is becoming a popular language for scientific applications and is increasingly used for high performance computing. In this course we want to introduce Matlab programmers to the usage of Python. Matlab and Python have a comparable language philosophy, but Python can offer better performance using its optimizations and parallelization interfaces. Python also increases the portability and flexibility (interaction with other open source and proprietary software packages) of solutions, and...

Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

DEFF Research Database (Denmark)

Hansen, Per Christian; Jensen, Søren Holdt

We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...... with working Matlab code and applications in speech processing....

BOLDSync: a MATLAB-based toolbox for synchronized stimulus presentation in functional MRI.

Science.gov (United States)

Joshi, Jitesh; Saharan, Sumiti; Mandal, Pravat K

2014-02-15

Precise and synchronized presentation of paradigm stimuli in functional magnetic resonance imaging (fMRI) is central to obtaining accurate information about brain regions involved in a specific task. In this manuscript, we present a new MATLAB-based toolbox, BOLDSync, for synchronized stimulus presentation in fMRI. BOLDSync provides a user friendly platform for design and presentation of visual, audio, as well as multimodal audio-visual (AV) stimuli in functional imaging experiments. We present simulation experiments that demonstrate the millisecond synchronization accuracy of BOLDSync, and also illustrate the functionalities of BOLDSync through application to an AV fMRI study. BOLDSync gains an advantage over other available proprietary and open-source toolboxes by offering a user friendly and accessible interface that affords both precision in stimulus presentation and versatility across various types of stimulus designs and system setups. BOLDSync is a reliable, efficient, and versatile solution for synchronized stimulus presentation in fMRI study. Copyright © 2013 Elsevier B.V. All rights reserved.

Updates to FuncLab, a Matlab based GUI for handling receiver functions

Science.gov (United States)

Porritt, Robert W.; Miller, Meghan S.

2018-02-01

Receiver functions are a versatile tool commonly used in seismic imaging. Depending on how they are processed, they can be used to image discontinuity structure within the crust or mantle or they can be inverted for seismic velocity either directly or jointly with complementary datasets. However, modern studies generally require large datasets which can be challenging to handle; therefore, FuncLab was originally written as an interactive Matlab GUI to assist in handling these large datasets. This software uses a project database to allow interactive trace editing, data visualization, H-κ stacking for crustal thickness and Vp/Vs ratio, and common conversion point stacking while minimizing computational costs. Since its initial release, significant advances have been made in the implementation of web services and changes in the underlying Matlab platform have necessitated a significant revision to the software. Here, we present revisions to the software, including new features such as data downloading via irisFetch.m, receiver function calculations via processRFmatlab, on-the-fly cross-section tools, interface picking, and more. In the descriptions of the tools, we present its application to a test dataset in Michigan, Wisconsin, and neighboring areas following the passage of USArray Transportable Array. The software is made available online at https://robporritt.wordpress.com/software.

Deterministic modelling and stochastic simulation of biochemical pathways using MATLAB.

Science.gov (United States)

Ullah, M; Schmidt, H; Cho, K H; Wolkenhauer, O

2006-03-01

The analysis of complex biochemical networks is conducted in two popular conceptual frameworks for modelling. The deterministic approach requires the solution of ordinary differential equations (ODEs, reaction rate equations) with concentrations as continuous state variables. The stochastic approach involves the simulation of differential-difference equations (chemical master equations, CMEs) with probabilities as variables. This is to generate counts of molecules for chemical species as realisations of random variables drawn from the probability distribution described by the CMEs. Although there are numerous tools available, many of them free, the modelling and simulation environment MATLAB is widely used in the physical and engineering sciences. We describe a collection of MATLAB functions to construct and solve ODEs for deterministic simulation and to implement realisations of CMEs for stochastic simulation using advanced MATLAB coding (Release 14). The program was successfully applied to pathway models from the literature for both cases. The results were compared to implementations using alternative tools for dynamic modelling and simulation of biochemical networks. The aim is to provide a concise set of MATLAB functions that encourage the experimentation with systems biology models. All the script files are available from www.sbi.uni-rostock.de/ publications_matlab-paper.html.

Introduction to fuzzy logic using Matlab

CERN Document Server

Sivanandam, SN; Deepa, S N

2006-01-01

Fuzzy Logic, at present is a hot topic, among academicians as well various programmers. This book is provided to give a broad, in-depth overview of the field of Fuzzy Logic. The basic principles of Fuzzy Logic are discussed in detail with various solved examples. The different approaches and solutions to the problems given in the book are well balanced and pertinent to the Fuzzy Logic research projects. The applications of Fuzzy Logic are also dealt to make the readers understand the concept of Fuzzy Logic. The solutions to the problems are programmed using MATLAB 6.0 and the simulated results are given. The MATLAB Fuzzy Logic toolbox is provided for easy reference.

A Method on Dynamic Path Planning for Robotic Manipulator Autonomous Obstacle Avoidance Based on an Improved RRT Algorithm.

Science.gov (United States)

Wei, Kun; Ren, Bingyin

2018-02-13

In a future intelligent factory, a robotic manipulator must work efficiently and safely in a Human-Robot collaborative and dynamic unstructured environment. Autonomous path planning is the most important issue which must be resolved first in the process of improving robotic manipulator intelligence. Among the path-planning methods, the Rapidly Exploring Random Tree (RRT) algorithm based on random sampling has been widely applied in dynamic path planning for a high-dimensional robotic manipulator, especially in a complex environment because of its probability completeness, perfect expansion, and fast exploring speed over other planning methods. However, the existing RRT algorithm has a limitation in path planning for a robotic manipulator in a dynamic unstructured environment. Therefore, an autonomous obstacle avoidance dynamic path-planning method for a robotic manipulator based on an improved RRT algorithm, called Smoothly RRT (S-RRT), is proposed. This method that targets a directional node extends and can increase the sampling speed and efficiency of RRT dramatically. A path optimization strategy based on the maximum curvature constraint is presented to generate a smooth and curved continuous executable path for a robotic manipulator. Finally, the correctness, effectiveness, and practicability of the proposed method are demonstrated and validated via a MATLAB static simulation and a Robot Operating System (ROS) dynamic simulation environment as well as a real autonomous obstacle avoidance experiment in a dynamic unstructured environment for a robotic manipulator. The proposed method not only provides great practical engineering significance for a robotic manipulator's obstacle avoidance in an intelligent factory, but also theoretical reference value for other type of robots' path planning.

An Open-source Toolbox for Analysing and Processing PhysioNet Databases in MATLAB and Octave.

Science.gov (United States)

Silva, Ikaro; Moody, George B

The WaveForm DataBase (WFDB) Toolbox for MATLAB/Octave enables integrated access to PhysioNet's software and databases. Using the WFDB Toolbox for MATLAB/Octave, users have access to over 50 physiological databases in PhysioNet. The toolbox provides access over 4 TB of biomedical signals including ECG, EEG, EMG, and PLETH. Additionally, most signals are accompanied by metadata such as medical annotations of clinical events: arrhythmias, sleep stages, seizures, hypotensive episodes, etc. Users of this toolbox should easily be able to reproduce, validate, and compare results published based on PhysioNet's software and databases.

MatLab 1a

DEFF Research Database (Denmark)

Kristiansen, Heidi; Kaas, Thomas; Freil, Ole

Bogen indeholder fire kapitler: ’Tæl og brug tal’, ’Undersøg figurer’, ’Plus- og minusproblemer’ og ’Statistik og chance’. MATLAB: •bygger på en undersøgende og problemorienteret tilgang til matematikken •understøtter læringsmålstyret undervisning •har fokus på faglige samtaler og undersøgelser...

ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

Science.gov (United States)

Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

2017-02-15

ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks. Freely available extension to ImageJ2 ( http://imagej.net/Downloads ). Installation and use instructions available at http://imagej.net/MATLAB_Scripting. Tested with ImageJ 2.0.0-rc-54 , Java 1.8.0_66 and MATLAB R2015b. eliceiri@wisc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

The Algorithm for Algorithms: An Evolutionary Algorithm Based on Automatic Designing of Genetic Operators

Directory of Open Access Journals (Sweden)

Dazhi Jiang

2015-01-01

Full Text Available At present there is a wide range of evolutionary algorithms available to researchers and practitioners. Despite the great diversity of these algorithms, virtually all of the algorithms share one feature: they have been manually designed. A fundamental question is “are there any algorithms that can design evolutionary algorithms automatically?” A more complete definition of the question is “can computer construct an algorithm which will generate algorithms according to the requirement of a problem?” In this paper, a novel evolutionary algorithm based on automatic designing of genetic operators is presented to address these questions. The resulting algorithm not only explores solutions in the problem space like most traditional evolutionary algorithms do, but also automatically generates genetic operators in the operator space. In order to verify the performance of the proposed algorithm, comprehensive experiments on 23 well-known benchmark optimization problems are conducted. The results show that the proposed algorithm can outperform standard differential evolution algorithm in terms of convergence speed and solution accuracy which shows that the algorithm designed automatically by computers can compete with the algorithms designed by human beings.

Genetic algorithm-based neural network for accidents diagnosis of research reactors on FPGA

International Nuclear Information System (INIS)

Ghuname, A.A.A.

2012-01-01

The Nuclear Research Reactors plants are expected to be operated with high levels of reliability, availability and safety. In order to achieve and maintain system stability and assure satisfactory and safe operation, there is increasing demand for automated systems to detect and diagnose such failures. Artificial Neural Networks (ANNs) are one of the most popular solutions because of their parallel structure, high speed, and their ability to give easy solution to complicated problems. The genetic algorithms (GAs) which are search algorithms (optimization techniques), in recent years, have been used to find the optimum construction of a neural network for definite application, as one of the advantages of its usage. Nowadays, Field Programmable Gate Arrays (FPGAs) are being an important implementation method of neural networks due to their high performance and they can easily be made parallel. The VHDL, which stands for VHSIC (Very High Speed Integrated Circuits) Hardware Description Language, have been used to describe the design behaviorally in addition to schematic and other description languages. The description of designs in synthesizable language such as VHDL make them reusable and be implemented in upgradeable systems like the Nuclear Research Reactors plants. In this thesis, the work was carried out through three main parts.In the first part, the Nuclear Research Reactors accident's pattern recognition is tackled within the artificial neural network approach. Such patterns are introduced initially without noise. And, to increase the reliability of such neural network, the noise ratio up to 50% was added for training in order to ensure the recognition of these patterns if it introduced with noise.The second part is concerned with the construction of Artificial Neural Networks (ANNs) using Genetic algorithms (GAs) for the nuclear accidents diagnosis. MATLAB ANNs toolbox and GAs toolbox are employed to optimize an ANN for this purpose. The results obtained show

Normalization based K means Clustering Algorithm

OpenAIRE

Virmani, Deepali; Taneja, Shweta; Malhotra, Geetika

2015-01-01

K-means is an effective clustering technique used to separate similar data into groups based on initial centroids of clusters. In this paper, Normalization based K-means clustering algorithm(N-K means) is proposed. Proposed N-K means clustering algorithm applies normalization prior to clustering on the available data as well as the proposed approach calculates initial centroids based on weights. Experimental results prove the betterment of proposed N-K means clustering algorithm over existing...

MatLab 0. Matematiklaboratoriet

DEFF Research Database (Denmark)

Kristiansen, Heidi; Kaas, Thomas; Freil, Ole

Bogen indeholder fem kapitler: ’Tælle og tal’, ’Figurer og mønstre’, ’Hvor mange?’, ’Måling’ og ’Data og diagrammer’. MATLAB: •bygger på en undersøgende og problemorienteret tilgang til matematikken •understøtter læringsmålstyret undervisning •har fokus på faglige samtaler og undersøgelser, der...

Piezoelectric Actuator Modeling Using MSC/NASTRAN and MATLAB

Science.gov (United States)

Reaves, Mercedes C.; Horta, Lucas G.

2003-01-01

This paper presents a procedure for modeling structures containing piezoelectric actuators using MSCMASTRAN and MATLAB. The paper describes the utility and functionality of one set of validated modeling tools. The tools described herein use MSCMASTRAN to model the structure with piezoelectric actuators and a thermally induced strain to model straining of the actuators due to an applied voltage field. MATLAB scripts are used to assemble the dynamic equations and to generate frequency response functions. The application of these tools is discussed using a cantilever aluminum beam with a surface mounted piezoelectric actuator as a sample problem. Software in the form of MSCINASTRAN DMAP input commands, MATLAB scripts, and a step-by-step procedure to solve the example problem are provided. Analysis results are generated in terms of frequency response functions from deflection and strain data as a function of input voltage to the actuator.

Introduction to multifractal detrended fluctuation analysis in matlab.

Science.gov (United States)

Ihlen, Espen A F

2012-01-01

Fractal structures are found in biomedical time series from a wide range of physiological phenomena. The multifractal spectrum identifies the deviations in fractal structure within time periods with large and small fluctuations. The present tutorial is an introduction to multifractal detrended fluctuation analysis (MFDFA) that estimates the multifractal spectrum of biomedical time series. The tutorial presents MFDFA step-by-step in an interactive Matlab session. All Matlab tools needed are available in Introduction to MFDFA folder at the website www.ntnu.edu/inm/geri/software. MFDFA are introduced in Matlab code boxes where the reader can employ pieces of, or the entire MFDFA to example time series. After introducing MFDFA, the tutorial discusses the best practice of MFDFA in biomedical signal processing. The main aim of the tutorial is to give the reader a simple self-sustained guide to the implementation of MFDFA and interpretation of the resulting multifractal spectra.

Stabilization Algorithms for Large-Scale Problems

DEFF Research Database (Denmark)

Jensen, Toke Koldborg

2006-01-01

The focus of the project is on stabilization of large-scale inverse problems where structured models and iterative algorithms are necessary for computing approximate solutions. For this purpose, we study various iterative Krylov methods and their abilities to produce regularized solutions. Some......-curve. This heuristic is implemented as a part of a larger algorithm which is developed in collaboration with G. Rodriguez and P. C. Hansen. Last, but not least, a large part of the project has, in different ways, revolved around the object-oriented Matlab toolbox MOORe Tools developed by PhD Michael Jacobsen. New...

Image quality evaluation of full reference algorithm

Science.gov (United States)

He, Nannan; Xie, Kai; Li, Tong; Ye, Yushan

2018-03-01

Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing them.MSE and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation ,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.

Introduction to Artificial Vision through Laboratory Guides Using Matlab

Directory of Open Access Journals (Sweden)

Verónica Londoño-Osorio

2013-11-01

Full Text Available This paper presents the design of two laboratory guides in artificial vision for a course which aims to introduce students to the different areas of specialization of his career. Therefore, the designed practices motivate and provide relevant content to the student, and to encourage research in the area of image processing. The first guide presents an introductory practice that explores the basic commands for image processing by programming a GUI in Matlab, and a second practice in which you use an image recognition algorithm, which compares the color characteristics of facial or objects images. The discussion of the results, challenges and recommendations for the development of each practice session are explained. The survey answers of the students are displayed. This survey allows checking their level of acceptance for the design and content of practice and motivation to continue studying in the image processing area. Finally, comparisons with laboratory guides that were designed in other universities are made.

Matlab Software for Spatial Panels

NARCIS (Netherlands)

Elhorst, J.Paul

2014-01-01

Elhorst provides Matlab routines to estimate spatial panel data models at his website. This article extends these routines to include the bias correction procedure proposed by Lee and Yu if the spatial panel data model contains spatial and/or time-period fixed effects, the direct and indirect

ECONOMIC MODELING PROCESSES USING MATLAB

Directory of Open Access Journals (Sweden)

Anamaria G. MACOVEI

2008-06-01

Full Text Available To study economic phenomena and processes using mathem atical modeling, and to determine the approximatesolution to a problem we need to choose a method of calculation and a numerical computer program, namely thepackage of programs MatLab. Any economic process or phenomenon is a mathematical description of h is behavior,and thus draw up an economic and mathematical model that has the following stages: formulation of the problem, theanalysis process modeling, the production model and design verification, validation and implementation of the model.This article is presented an economic model and its modeling is using mathematical equations and software packageMatLab, which helps us approximation effective solution. As data entry is considered the net cost, the cost of direct andtotal cost and the link between them. I presented the basic formula for determining the total cost. Economic modelcalculations were made in MatLab software package and with graphic representation of its interpretation of the resultsachieved in terms of our specific problem.

Recognition of Wheat Spike from Field Based Phenotype Platform Using Multi-Sensor Fusion and Improved Maximum Entropy Segmentation Algorithms

Directory of Open Access Journals (Sweden)

Chengquan Zhou

2018-02-01

Full Text Available To obtain an accurate count of wheat spikes, which is crucial for estimating yield, this paper proposes a new algorithm that uses computer vision to achieve this goal from an image. First, a home-built semi-autonomous multi-sensor field-based phenotype platform (FPP is used to obtain orthographic images of wheat plots at the filling stage. The data acquisition system of the FPP provides high-definition RGB images and multispectral images of the corresponding quadrats. Then, the high-definition panchromatic images are obtained by fusion of three channels of RGB. The Gram–Schmidt fusion algorithm is then used to fuse these multispectral and panchromatic images, thereby improving the color identification degree of the targets. Next, the maximum entropy segmentation method is used to do the coarse-segmentation. The threshold of this method is determined by a firefly algorithm based on chaos theory (FACT, and then a morphological filter is used to de-noise the coarse-segmentation results. Finally, morphological reconstruction theory is applied to segment the adhesive part of the de-noised image and realize the fine-segmentation of the image. The computer-generated counting results for the wheat plots, using independent regional statistical function in Matlab R2017b software, are then compared with field measurements which indicate that the proposed method provides a more accurate count of wheat spikes when compared with other traditional fusion and segmentation methods mentioned in this paper.

Application of Fuzzy Algorithm in Optimizing Hierarchical Sliding Mode Control for Pendubot System

Directory of Open Access Journals (Sweden)

Xuan Dung Huynh

2017-12-01

Full Text Available Pendubot is a classical under-actuated SIMO model for control algorithm testing in laboratory of universities. In this paper, authors design a fuzzy-sliding control for this system. The controller is designed from a new idea of application of fuzzy algorithm for optioning control parameters. The response of system on TOP position under fuzzysliding control algorithm is proved to be better than under sliding controller through Matlab/Simulink simulation.

A Matlab program for stepwise regression

Directory of Open Access Journals (Sweden)

Yanhong Qi

2016-03-01

Full Text Available The stepwise linear regression is a multi-variable regression for identifying statistically significant variables in the linear regression equation. In present study, we presented the Matlab program of stepwise regression.

Resource efficient data compression algorithms for demanding, WSN based biomedical applications.

Science.gov (United States)

Antonopoulos, Christos P; Voros, Nikolaos S

2016-02-01

During the last few years, medical research areas of critical importance such as Epilepsy monitoring and study, increasingly utilize wireless sensor network technologies in order to achieve better understanding and significant breakthroughs. However, the limited memory and communication bandwidth offered by WSN platforms comprise a significant shortcoming to such demanding application scenarios. Although, data compression can mitigate such deficiencies there is a lack of objective and comprehensive evaluation of relative approaches and even more on specialized approaches targeting specific demanding applications. The research work presented in this paper focuses on implementing and offering an in-depth experimental study regarding prominent, already existing as well as novel proposed compression algorithms. All algorithms have been implemented in a common Matlab framework. A major contribution of this paper, that differentiates it from similar research efforts, is the employment of real world Electroencephalography (EEG) and Electrocardiography (ECG) datasets comprising the two most demanding Epilepsy modalities. Emphasis is put on WSN applications, thus the respective metrics focus on compression rate and execution latency for the selected datasets. The evaluation results reveal significant performance and behavioral characteristics of the algorithms related to their complexity and the relative negative effect on compression latency as opposed to the increased compression rate. It is noted that the proposed schemes managed to offer considerable advantage especially aiming to achieve the optimum tradeoff between compression rate-latency. Specifically, proposed algorithm managed to combine highly completive level of compression while ensuring minimum latency thus exhibiting real-time capabilities. Additionally, one of the proposed schemes is compared against state-of-the-art general-purpose compression algorithms also exhibiting considerable advantages as far as the

Matlab GUI for a Fluid Mixer

Science.gov (United States)

Barbieri, Enrique

2005-01-01

The Test and Engineering Directorate at NASA John C. Stennis Space Center developed an interest to study the modeling, evaluation, and control of a liquid hydrogen (LH2) and gas hydrogen (GH2) mixer subsystem of a ground test facility. This facility carries out comprehensive ground-based testing and certification of liquid rocket engines including the Space Shuttle Main engine. A software simulation environment developed in MATLAB/SIMULINK (M/S) will allow NASA engineers to test rocket engine systems at relatively no cost. In the progress report submitted in February 2004, we described the development of two foundation programs, a reverse look-up application using various interpolation algorithms, a variety of search and return methods, and self-checking methods to reduce the error in returned search results to increase the functionality of the program. The results showed that these efforts were successful. To transfer this technology to engineers who are not familiar with the M/S environment, a four-module GUI was implemented allowing the user to evaluate the mixer model under open-loop and closed-loop conditions. The progress report was based on an udergraduate Honors Thesis by Ms. Jamie Granger Austin in the Department of Electrical Engineering and Computer Science at Tulane University, during January-May 2003, and her continued efforts during August-December 2003. In collaboration with Dr. Hanz Richter and Dr. Fernando Figueroa we published these results in a NASA Tech Brief due to appear this year. Although the original proposal in 2003 did not address other components of the test facility, we decided in the last few months to extend our research and consider a related pressurization tank component as well. This report summarizes the results obtained towards a Graphical User Interface (GUI) for the evaluation and control of the hydrogen mixer subsystem model and for the pressurization tank each taken individually. Further research would combine the two

Signals and systems with MATLAB

CERN Document Server

Yang, Won Young; Song, Ik H; Cho, Yong S

2009-01-01

Covers some of the theoretical foundations and mathematical derivations that can be used in higher-level related subjects such as signal processing, communication, and control, minimizing the mathematical difficulty and computational burden. This book illustrates the usage of MATLAB and Simulink for signal and system analysis and design.

User Guide for Compressible Flow Toolbox Version 2.1 for Use With MATLAB(Registered Trademark); Version 7

Science.gov (United States)

Melcher, Kevin J.

2006-01-01

This report provides a user guide for the Compressible Flow Toolbox, a collection of algorithms that solve almost 300 linear and nonlinear classical compressible flow relations. The algorithms, implemented in the popular MATLAB programming language, are useful for analysis of one-dimensional steady flow with constant entropy, friction, heat transfer, or shock discontinuities. The solutions do not include any gas dissociative effects. The toolbox also contains functions for comparing and validating the equation-solving algorithms against solutions previously published in the open literature. The classical equations solved by the Compressible Flow Toolbox are: isentropic-flow equations, Fanno flow equations (pertaining to flow of an ideal gas in a pipe with friction), Rayleigh flow equations (pertaining to frictionless flow of an ideal gas, with heat transfer, in a pipe of constant cross section.), normal-shock equations, oblique-shock equations, and Prandtl-Meyer expansion equations. At the time this report was published, the Compressible Flow Toolbox was available without cost from the NASA Software Repository.

Computer Based Learning in an Undergraduate Physics Laboratory: Interfacing and Instrument Control Using Matlab

Science.gov (United States)

Sharp, J. S.; Glover, P. M.; Moseley, W.

2007-01-01

In this paper we describe the recent changes to the curriculum of the second year practical laboratory course in the School of Physics and Astronomy at the University of Nottingham. In particular, we describe how Matlab has been implemented as a teaching tool and discuss both its pedagogical advantages and disadvantages in teaching undergraduate…

[An automatic color correction algorithm for digital human body sections].

Science.gov (United States)

Zhuge, Bin; Zhou, He-qin; Tang, Lei; Lang, Wen-hui; Feng, Huan-qing

2005-06-01

To find a new approach to improve the uniformity of color parameters for images data of the serial sections of the human body. An auto-color correction algorithm in the RGB color space based on a standard CMYK color chart was proposed. The gray part of the color chart was auto-segmented from every original image, and fifteen gray values were attained. The transformation function between the measured gray value and the standard gray value of the color chart and the lookup table were obtained. In RGB color space, the colors of images were corrected according to the lookup table. The color of original Chinese Digital Human Girl No. 1 (CDH-G1) database was corrected by using the algorithm with Matlab 6.5, and it took 13.475 s to deal with one picture on a personal computer. Using the algorithm, the color of the original database is corrected automatically and quickly. The uniformity of color parameters for corrected dataset is improved.

Marine Traffic Optimization Using Petri Net and Genetic Algorithm

Directory of Open Access Journals (Sweden)

Anita Gudelj

2012-11-01

Full Text Available The paper deals with the traffic control and job optimization in the marine canal system. The moving of vessels can be described as a set of discrete events and states. Some of these states can be undesirable such as conflicts and deadlocks. It is necessary to apply adequate control policy to avoid deadlocks and blocks the vessels’ moving only in the case of dangerous situation. This paper addresses the use of Petri net as modelling and scheduling tool in this context. To find better solutions the authors propose the integration of Petri net with a genetic algorithm. Also, a matrix based formal method is proposed for analyzing discrete event dynamic system (DEDS. The algorithm is developed to deal with multi-project, multi-constrained scheduling problem with shared resources. It is verified by a computer simulation using MATLAB environment.

Wavelet-LMS algorithm-based echo cancellers

Science.gov (United States)

Seetharaman, Lalith K.; Rao, Sathyanarayana S.

2002-12-01

This paper presents Echo Cancellers based on the Wavelet-LMS Algorithm. The performance of the Least Mean Square Algorithm in Wavelet transform domain is observed and its application in Echo cancellation is analyzed. The Widrow-Hoff Least Mean Square Algorithm is most widely used algorithm for Adaptive filters that function as Echo Cancellers. The present day communication signals are widely non-stationary in nature and some errors crop up when Least Mean Square Algorithm is used for the Echo Cancellers handling such signals. The analysis of non-stationary signals often involves a compromise between how well transitions or discontinuities can be located. The multi-scale or multi-resolution of signal analysis, which is the essence of wavelet transform, makes Wavelets popular in non-stationary signal analysis. In this paper, we present a Wavelet-LMS algorithm wherein the wavelet coefficients of a signal are modified adaptively using the Least Mean Square Algorithm and then reconstructed to give an Echo-free signal. The Echo Canceller based on this Algorithm is found to have a better convergence and a comparatively lesser MSE (Mean Square error).

Glowworm swarm optimization theory, algorithms, and applications

CERN Document Server

Kaipa, Krishnanand N

2017-01-01

This book provides a comprehensive account of the glowworm swarm optimization (GSO) algorithm, including details of the underlying ideas, theoretical foundations, algorithm development, various applications, and MATLAB programs for the basic GSO algorithm. It also discusses several research problems at different levels of sophistication that can be attempted by interested researchers. The generality of the GSO algorithm is evident in its application to diverse problems ranging from optimization to robotics. Examples include computation of multiple optima, annual crop planning, cooperative exploration, distributed search, multiple source localization, contaminant boundary mapping, wireless sensor networks, clustering, knapsack, numerical integration, solving fixed point equations, solving systems of nonlinear equations, and engineering design optimization. The book is a valuable resource for researchers as well as graduate and undergraduate students in the area of swarm intelligence and computational intellige...

An Elementary Algorithm to Evaluate Trigonometric Functions to High Precision

Science.gov (United States)

Johansson, B. Tomas

2018-01-01

Evaluation of the cosine function is done via a simple Cordic-like algorithm, together with a package for handling arbitrary-precision arithmetic in the computer program Matlab. Approximations to the cosine function having hundreds of correct decimals are presented with a discussion around errors and implementation.

Analytic reconstruction algorithms for triple-source CT with horizontal data truncation

International Nuclear Information System (INIS)

Chen, Ming; Yu, Hengyong

2015-01-01

Purpose: This paper explores a triple-source imaging method with horizontal data truncation to enlarge the field of view (FOV) for big objects. Methods: The study is conducted by using theoretical analysis, mathematical deduction, and numerical simulations. The proposed algorithms are implemented in c + + and MATLAB. While the basic platform is constructed in MATLAB, the computationally intensive segments are coded in c + +, which are linked via a MEX interface. Results: A triple-source circular scanning configuration with horizontal data truncation is developed, where three pairs of x-ray sources and detectors are unevenly distributed on the same circle to cover the whole imaging object. For this triple-source configuration, a fan-beam filtered backprojection-type algorithm is derived for truncated full-scan projections without data rebinning. The algorithm is also extended for horizontally truncated half-scan projections and cone-beam projections in a Feldkamp-type framework. Using their method, the FOV is enlarged twofold to threefold to scan bigger objects with high speed and quality. The numerical simulation results confirm the correctness and effectiveness of the developed algorithms. Conclusions: The triple-source scanning configuration with horizontal data truncation cannot only keep most of the advantages of a traditional multisource system but also cover a larger FOV for big imaging objects. In addition, because the filtering is shift-invariant, the proposed algorithms are very fast and easily parallelized on graphic processing units

STEGANOGRAPHY FOR TWO AND THREE LSBs USING EXTENDED SUBSTITUTION ALGORITHM

Directory of Open Access Journals (Sweden)

R.S. Gutte

2013-03-01

Full Text Available The Security of data on internet has become a prior thing. Though any message is encrypted using a stronger cryptography algorithm, it cannot avoid the suspicion of intruder. This paper proposes an approach in such way that, data is encrypted using Extended Substitution Algorithm and then this cipher text is concealed at two or three LSB positions of the carrier image. This algorithm covers almost all type of symbols and alphabets. The encrypted text is concealed variably into the LSBs. Therefore, it is a stronger approach. The visible characteristics of the carrier image before and after concealment remained almost the same. The algorithm has been implemented using Matlab.

Model-independent nonlinear control algorithm with application to a liquid bridge experiment

International Nuclear Information System (INIS)

Petrov, V.; Haaning, A.; Muehlner, K.A.; Van Hook, S.J.; Swinney, H.L.

1998-01-01

We present a control method for high-dimensional nonlinear dynamical systems that can target remote unstable states without a priori knowledge of the underlying dynamical equations. The algorithm constructs a high-dimensional look-up table based on the system's responses to a sequence of random perturbations. The method is demonstrated by stabilizing unstable flow of a liquid bridge surface-tension-driven convection experiment that models the float zone refining process. Control of the dynamics is achieved by heating or cooling two thermoelectric Peltier devices placed in the vicinity of the liquid bridge surface. The algorithm routines along with several example programs written in the MATLAB language can be found at ftp://ftp.mathworks.com/pub/contrib/v5/control/nlcontrol. copyright 1998 The American Physical Society

Elements of matrix modeling and computing with Matlab

CERN Document Server

White, Robert E

2006-01-01

As discrete models and computing have become more common, there is a need to study matrix computation and numerical linear algebra. Encompassing a diverse mathematical core, Elements of Matrix Modeling and Computing with MATLAB examines a variety of applications and their modeling processes, showing you how to develop matrix models and solve algebraic systems. Emphasizing practical skills, it creates a bridge from problems with two and three variables to more realistic problems that have additional variables. Elements of Matrix Modeling and Computing with MATLAB focuses on seven basic applicat

Estimating aquifer transmissivity from specific capacity using MATLAB.

Science.gov (United States)

McLin, Stephen G

2005-01-01

Historically, specific capacity information has been used to calculate aquifer transmissivity when pumping test data are unavailable. This paper presents a simple computer program written in the MATLAB programming language that estimates transmissivity from specific capacity data while correcting for aquifer partial penetration and well efficiency. The program graphically plots transmissivity as a function of these factors so that the user can visually estimate their relative importance in a particular application. The program is compatible with any computer operating system running MATLAB, including Windows, Macintosh OS, Linux, and Unix. Two simple examples illustrate program usage.

An efficient IMPES-based, shifting matrix algorithm to simulate two-phase, immiscible flow in porous media with application to CO 2 sequestration in the subsurface

KAUST Repository

Salama, Amgad

2012-01-01

The flow of two or more immiscible fluids in porous media is ubiquitous particularly in oil industry. This includes secondary and tertiary oil recovery, CO2 sequestration, etc. Accurate predictions of the development of these processes are important in estimating the benefits, e.g., in the form of increased oil extraction, when using certain technology. However, this accurate prediction depends to a large extent on two things; the first is related to our ability to correctly characterize the reservoir with all its complexities and the second depends on our ability to develop robust techniques that solve the governing equations efficiently and accurately. In this work, we introduce a new robust and efficient numerical technique to solving the governing conservation laws which govern the movement of two immiscible fluids in the subsurface. This work will be applied to the problem of CO2 sequestration in deep saline aquifer; however, it can also be extended to incorporate more cases. The traditional solution algorithms to this problem are based on discretizing the governing laws on a generic cell and then proceed to the other cells within loops. Therefore, it is expected that, calling and iterating these loops several times can take significant amount of CPU time. Furthermore, if this process is done using programming languages which require repeated interpretation each time a loop is called like Matlab, Python or the like, extremely longer time is expected particularly for larger systems. In this new algorithm, the solution is done for all the nodes at once and not within loops. The solution methodology involves manipulating all the variables as column vectors. Then using shifting matrices, these vectors are sifted in such a way that subtracting relevant vectors produces the corresponding difference algorithm. It has been found that this technique significantly reduces the amount of CPU times compared with traditional technique implemented within the framework of

System engineering approach to GPM retrieval algorithms

Energy Technology Data Exchange (ETDEWEB)

Rose, C. R. (Chris R.); Chandrasekar, V.

2004-01-01

calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.

MATLAB/SIMULINK platform for simulation of CANDU reactor control system

International Nuclear Information System (INIS)

Javidnia, H.; Jiang, J.

2007-01-01

In this paper a simulation platform for CANDU reactors' control system is presented. The platform is built on MATLAB/SIMULINK interactive graphical interface. Since MATLAB/SIMULINK are powerful tools to describe systems mathematically, all the subsystems in a CANDU reactor are represented in MATLAB's language and are implemented in SIMULINK graphical representation. The focus of the paper is on the flux control loop of CANDU reactors. However, the ideas can be extended to include other parts in CANDU power plants and the same technique can be applied to other types of nuclear reactors and their control systems. The CANDU reactor model and xenon feedback model are also discussed in this paper. (author)

Hidden markov model for the prediction of transmembrane proteins using MATLAB.

Science.gov (United States)

Chaturvedi, Navaneet; Shanker, Sudhanshu; Singh, Vinay Kumar; Sinha, Dhiraj; Pandey, Paras Nath

2011-01-01

Since membranous proteins play a key role in drug targeting therefore transmembrane proteins prediction is active and challenging area of biological sciences. Location based prediction of transmembrane proteins are significant for functional annotation of protein sequences. Hidden markov model based method was widely applied for transmembrane topology prediction. Here we have presented a revised and a better understanding model than an existing one for transmembrane protein prediction. Scripting on MATLAB was built and compiled for parameter estimation of model and applied this model on amino acid sequence to know the transmembrane and its adjacent locations. Estimated model of transmembrane topology was based on TMHMM model architecture. Only 7 super states are defined in the given dataset, which were converted to 96 states on the basis of their length in sequence. Accuracy of the prediction of model was observed about 74 %, is a good enough in the area of transmembrane topology prediction. Therefore we have concluded the hidden markov model plays crucial role in transmembrane helices prediction on MATLAB platform and it could also be useful for drug discovery strategy. The database is available for free at bioinfonavneet@gmail.comvinaysingh@bhu.ac.in.

FPGA based hardware optimized implementation of signal processing system for LFM pulsed radar

Science.gov (United States)

Azim, Noor ul; Jun, Wang

2016-11-01

Signal processing is one of the main parts of any radar system. Different signal processing algorithms are used to extract information about different parameters like range, speed, direction etc, of a target in the field of radar communication. This paper presents LFM (Linear Frequency Modulation) pulsed radar signal processing algorithms which are used to improve target detection, range resolution and to estimate the speed of a target. Firstly, these algorithms are simulated in MATLAB to verify the concept and theory. After the conceptual verification in MATLAB, the simulation is converted into implementation on hardware using Xilinx FPGA. Chosen FPGA is Xilinx Virtex-6 (XC6LVX75T). For hardware implementation pipeline optimization is adopted and also other factors are considered for resources optimization in the process of implementation. Focusing algorithms in this work for improving target detection, range resolution and speed estimation are hardware optimized fast convolution processing based pulse compression and pulse Doppler processing.

TecLines: A MATLAB-Based Toolbox for Tectonic Lineament Analysis from Satellite Images and DEMs, Part 1: Line Segment Detection and Extraction

Directory of Open Access Journals (Sweden)

Mehdi Rahnama

2014-06-01

Full Text Available Geological structures, such as faults and fractures, appear as image discontinuities or lineaments in remote sensing data. Geologic lineament mapping is a very important issue in geo-engineering, especially for construction site selection, seismic, and risk assessment, mineral exploration and hydrogeological research. Classical methods of lineaments extraction are based on semi-automated (or visual interpretation of optical data and digital elevation models. We developed a freely available Matlab based toolbox TecLines (Tectonic Lineament Analysis for locating and quantifying lineament patterns using satellite data and digital elevation models. TecLines consists of a set of functions including frequency filtering, spatial filtering, tensor voting, Hough transformation, and polynomial fitting. Due to differences in the mathematical background of the edge detection and edge linking procedure as well as the breadth of the methods, we introduce the approach in two-parts. In this first study, we present the steps that lead to edge detection. We introduce the data pre-processing using selected filters in spatial and frequency domains. We then describe the application of the tensor-voting framework to improve position and length accuracies of the detected lineaments. We demonstrate the robustness of the approach in a complex area in the northeast of Afghanistan using a panchromatic QUICKBIRD-2 image with 1-meter resolution. Finally, we compare the results of TecLines with manual lineament extraction, and other lineament extraction algorithms, as well as a published fault map of the study area.

Fundamentals of bioinformatics and computational biology methods and exercises in matlab

CERN Document Server

Singh, Gautam B

2015-01-01

This book offers comprehensive coverage of all the core topics of bioinformatics, and includes practical examples completed using the MATLAB bioinformatics toolbox™. It is primarily intended as a textbook for engineering and computer science students attending advanced undergraduate and graduate courses in bioinformatics and computational biology. The book develops bioinformatics concepts from the ground up, starting with an introductory chapter on molecular biology and genetics. This chapter will enable physical science students to fully understand and appreciate the ultimate goals of applying the principles of information technology to challenges in biological data management, sequence analysis, and systems biology. The first part of the book also includes a survey of existing biological databases, tools that have become essential in today’s biotechnology research. The second part of the book covers methodologies for retrieving biological information, including fundamental algorithms for sequence compar...

Prototype Implementation of Two Efficient Low-Complexity Digital Predistortion Algorithms

Directory of Open Access Journals (Sweden)

Timo I. Laakso

2008-01-01

Full Text Available Predistortion (PD lineariser for microwave power amplifiers (PAs is an important topic of research. With larger and larger bandwidth as it appears today in modern WiMax standards as well as in multichannel base stations for 3GPP standards, the relatively simple nonlinear effect of a PA becomes a complex memory-including function, severely distorting the output signal. In this contribution, two digital PD algorithms are investigated for the linearisation of microwave PAs in mobile communications. The first one is an efficient and low-complexity algorithm based on a memoryless model, called the simplicial canonical piecewise linear (SCPWL function that describes the static nonlinear characteristic of the PA. The second algorithm is more general, approximating the pre-inverse filter of a nonlinear PA iteratively using a Volterra model. The first simpler algorithm is suitable for compensation of amplitude compression and amplitude-to-phase conversion, for example, in mobile units with relatively small bandwidths. The second algorithm can be used to linearise PAs operating with larger bandwidths, thus exhibiting memory effects, for example, in multichannel base stations. A measurement testbed which includes a transmitter-receiver chain with a microwave PA is built for testing and prototyping of the proposed PD algorithms. In the testing phase, the PD algorithms are implemented using MATLAB (floating-point representation and tested in record-and-playback mode. The iterative PD algorithm is then implemented on a Field Programmable Gate Array (FPGA using fixed-point representation. The FPGA implementation allows the pre-inverse filter to be tested in a real-time mode. Measurement results show excellent linearisation capabilities of both the proposed algorithms in terms of adjacent channel power suppression. It is also shown that the fixed-point FPGA implementation of the iterative algorithm performs as well as the floating-point implementation.

Hybrid employment recommendation algorithm based on Spark

Science.gov (United States)

Li, Zuoquan; Lin, Yubei; Zhang, Xingming

2017-08-01

Aiming at the real-time application of collaborative filtering employment recommendation algorithm (CF), a clustering collaborative filtering recommendation algorithm (CCF) is developed, which applies hierarchical clustering to CF and narrows the query range of neighbour items. In addition, to solve the cold-start problem of content-based recommendation algorithm (CB), a content-based algorithm with users’ information (CBUI) is introduced for job recommendation. Furthermore, a hybrid recommendation algorithm (HRA) which combines CCF and CBUI algorithms is proposed, and implemented on Spark platform. The experimental results show that HRA can overcome the problems of cold start and data sparsity, and achieve good recommendation accuracy and scalability for employment recommendation.

Aplikasi MATLAB untuk Mengenali Karakter Tulisan Tangan

Directory of Open Access Journals (Sweden)

ali mahmudi

2017-03-01

Full Text Available Handwriting recognition is one of the very interesting research object in the field of image processing, artificial intelligence and computer vision. This is due to the handwritten characters is varied in every individual. The style, size and orientation of handwriting characters has made every body’s is different, hence handwriting recognition is a very interesting research object. Handwriting recognition application has been used in quite many applications, such as reading the bank deposits, reading the postal code in letters, and helping peolple in managing documents. This paper presents a handwriting recognition application using Matlab. Matlab toolbox that is used in this research are Image Processing and Neural Network Toolbox.

A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model.

Science.gov (United States)

Wijetunge, Chalini D; Saeed, Isaam; Boughton, Berin A; Roessner, Ute; Halgamuge, Saman K

2015-01-01

Mass Spectrometry (MS) is a ubiquitous analytical tool in biological research and is used to measure the mass-to-charge ratio of bio-molecules. Peak detection is the essential first step in MS data analysis. Precise estimation of peak parameters such as peak summit location and peak area are critical to identify underlying bio-molecules and to estimate their abundances accurately. We propose a new method to detect and quantify peaks in mass spectra. It uses dual-tree complex wavelet transformation along with Stein's unbiased risk estimator for spectra smoothing. Then, a new method, based on the modified Asymmetric Pseudo-Voigt (mAPV) model and hierarchical particle swarm optimization, is used for peak parameter estimation. Using simulated data, we demonstrated the benefit of using the mAPV model over Gaussian, Lorentz and Bi-Gaussian functions for MS peak modelling. The proposed mAPV model achieved the best fitting accuracy for asymmetric peaks, with lower percentage errors in peak summit location estimation, which were 0.17% to 4.46% less than that of the other models. It also outperformed the other models in peak area estimation, delivering lower percentage errors, which were about 0.7% less than its closest competitor - the Bi-Gaussian model. In addition, using data generated from a MALDI-TOF computer model, we showed that the proposed overall algorithm outperformed the existing methods mainly in terms of sensitivity. It achieved a sensitivity of 85%, compared to 77% and 71% of the two benchmark algorithms, continuous wavelet transformation based method and Cromwell respectively. The proposed algorithm is particularly useful for peak detection and parameter estimation in MS data with overlapping peak distributions and asymmetric peaks. The algorithm is implemented using MATLAB and the source code is freely available at http://mapv.sourceforge.net.

mGrid: A load-balanced distributed computing environment for the remote execution of the user-defined Matlab code

Directory of Open Access Journals (Sweden)

Almeida Jonas S

2006-03-01

Full Text Available Abstract Background Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. Results mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else. Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Conclusion Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based

mGrid: a load-balanced distributed computing environment for the remote execution of the user-defined Matlab code.

Science.gov (United States)

Karpievitch, Yuliya V; Almeida, Jonas S

2006-03-15

Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over

Matlab for electrical and computer engineering students and professionals with Simulink

CERN Document Server

Priemer, Roland

2013-01-01

This book combines the teaching of the MATLAB#65533; programming language with the presentation and development of carefully selected electrical and computer engineering (ECE) fundamentals. This is what distinguishes it from other books concerned with MATLAB#65533;: it is directed specifically to ECE concerns.

Scilab and MATLAB Interfaces to MUMPS (version 4.6 or greater)

OpenAIRE

Fèvre , Aurélia; Pralet , Stéphane; L'Excellent , Jean-Yves

2006-01-01

This document describes the Scilab and MATLAB interfaces to MUMPS version 4.6. We describe the differences and similarities between usual Fortran/C MUMPS interfaces and its Scilab/MATLAB interfaces, the calling sequences and functionalities. Examples of use and experimental results are also provided.

Development of MATLAB Scripts for the Calculation of Thermal Manikin Regional Resistance Values

Science.gov (United States)

2016-01-01

TECHNICAL NOTE NO. TN16-1 DATE January 2016 ADA DEVELOPMENT OF MATLAB ® SCRIPTS FOR THE...USARIEM TECHNICAL NOTE TN16-1 DEVELOPMENT OF MATLAB ® SCRIPTS FOR THE CALCULATION OF THERMAL MANIKIN REGIONAL RESISTANCE VALUES...EXECUTIVE SUMMARY A software tool has been developed via MATLAB ® scripts to reduce the amount of repetitive and time-consuming calculations that are

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

Science.gov (United States)

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

Artificial Neural Network Based State Estimators Integrated into Kalmtool

DEFF Research Database (Denmark)

Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

2012-01-01

In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as...

Short Project-Based Learning with MATLAB Applications to Support the Learning of Video-Image Processing

Science.gov (United States)

Gil, Pablo

2017-10-01

University courses concerning Computer Vision and Image Processing are generally taught using a traditional methodology that is focused on the teacher rather than on the students. This approach is consequently not effective when teachers seek to attain cognitive objectives involving their students' critical thinking. This manuscript covers the development, implementation and assessment of a short project-based engineering course with MATLAB applications Multimedia Engineering being taken by Bachelor's degree students. The principal goal of all course lectures and hands-on laboratory activities was for the students to not only acquire image-specific technical skills but also a general knowledge of data analysis so as to locate phenomena in pixel regions of images and video frames. This would hopefully enable the students to develop skills regarding the implementation of the filters, operators, methods and techniques used for image processing and computer vision software libraries. Our teaching-learning process thus permits the accomplishment of knowledge assimilation, student motivation and skill development through the use of a continuous evaluation strategy to solve practical and real problems by means of short projects designed using MATLAB applications. Project-based learning is not new. This approach has been used in STEM learning in recent decades. But there are many types of projects. The aim of the current study is to analyse the efficacy of short projects as a learning tool when compared to long projects during which the students work with more independence. This work additionally presents the impact of different types of activities, and not only short projects, on students' overall results in this subject. Moreover, a statistical study has allowed the author to suggest a link between the students' success ratio and the type of content covered and activities completed on the course. The results described in this paper show that those students who took part

Numerical modelling of suspended radioactive sediment transport in a stream using matlab

International Nuclear Information System (INIS)

Sarpong, Linda

2017-07-01

The use of materials that contain radioactive substances has gained grounds in Ghana due to numerous benefits derived from them. These radioactive materials can be found in the areas of medicine, agriculture and industries such as mining. Though there are strict measures to ensure such material do not find its way into the environment, improper management of the waste poses a threat to the environment. To be able to understand the impact the radioactive material has on the environment, mathematical models play a very relevant role in tracking the level of pollution in any medium. This thesis was concerned with the numerical modelling for the transport of the radioactive solute material that suspends in a stream using Matlab at different velocities as a result of flooding or an accident for research purposes. The modelling was done by using partial differential equations describing relevant physical processes evolution which includes water level, dissolved and suspended substances concentration and velocities. The equation system basis are the mass conservation and momentum laws, state equation and state transport equations. The implicit finite difference scheme was used to evaluate the transport equation, Advection-Dispersion Equation (ADE) with respect to time and space. Solution algorithms for Matlab programming were developed and implemented for generating results for analysis. The results obtained showed that the model was able to simulate accurately the various levels of suspended radioactive sediment concentration changes in the flowing stream longitudinally. (au)

A new hybrid genetic algorithm for optimizing the single and multivariate objective functions

Energy Technology Data Exchange (ETDEWEB)

Tumuluru, Jaya Shankar [Idaho National Laboratory; McCulloch, Richard Chet James [Idaho National Laboratory

2015-07-01

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the most improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.

Implementation of Period-Finding Algorithm by Means of Simulating Quantum Fourier Transform

Directory of Open Access Journals (Sweden)

Zohreh Moghareh Abed

2010-01-01

Full Text Available In this paper, we introduce quantum fourier transform as a key ingredient for many useful algorithms. These algorithms make a solution for problems which is considered to be intractable problems on a classical computer. Quantum Fourier transform is propounded as a key for quantum phase estimation algorithm. In this paper our aim is the implementation of period-finding algorithm.Quantum computer solves this problem, exponentially faster than classical one. Quantum phase estimation algorithm is the key for the period-finding problem .Therefore, by means of simulating quantum Fourier transform, we are able to implement the period-finding algorithm. In this paper, the simulation of quantum Fourier transform is carried out by Matlab software.

How to Interface Fortran with Matlab

OpenAIRE

Sagastizábal , Claudia; Vige , Guillaume

1995-01-01

Projet PROMATH; We describe the general procedure for interfacing Fortran routines with Matlab. We explain how to write a mex-file and the associated gateway function. In particular, each different type of argument is considered in detail. We finish with an illustrative example

Object-oriented Matlab adaptive optics toolbox

Science.gov (United States)

Conan, R.; Correia, C.

2014-08-01

Object-Oriented Matlab Adaptive Optics (OOMAO) is a Matlab toolbox dedicated to Adaptive Optics (AO) systems. OOMAO is based on a small set of classes representing the source, atmosphere, telescope, wavefront sensor, Deformable Mirror (DM) and an imager of an AO system. This simple set of classes allows simulating Natural Guide Star (NGS) and Laser Guide Star (LGS) Single Conjugate AO (SCAO) and tomography AO systems on telescopes up to the size of the Extremely Large Telescopes (ELT). The discrete phase screens that make the atmosphere model can be of infinite size, useful for modeling system performance on large time scales. OOMAO comes with its own parametric influence function model to emulate different types of DMs. The cone effect, altitude thickness and intensity profile of LGSs are also reproduced. Both modal and zonal modeling approach are implemented. OOMAO has also an extensive library of theoretical expressions to evaluate the statistical properties of turbulence wavefronts. The main design characteristics of the OOMAO toolbox are object-oriented modularity, vectorized code and transparent parallel computing. OOMAO has been used to simulate and to design the Multi-Object AO prototype Raven at the Subaru telescope and the Laser Tomography AO system of the Giant Magellan Telescope. In this paper, a Laser Tomography AO system on an ELT is simulated with OOMAO. In the first part, we set-up the class parameters and we link the instantiated objects to create the source optical path. Then we build the tomographic reconstructor and write the script for the pseudo-open-loop controller.

Image enhancement using MCNP5 code and MATLAB in neutron radiography.

Science.gov (United States)

Tharwat, Montaser; Mohamed, Nader; Mongy, T

2014-07-01

This work presents a method that can be used to enhance the neutron radiography (NR) image for objects with high scattering materials like hydrogen, carbon and other light materials. This method used Monte Carlo code, MCNP5, to simulate the NR process and get the flux distribution for each pixel of the image and determines the scattered neutron distribution that caused image blur, and then uses MATLAB to subtract this scattered neutron distribution from the initial image to improve its quality. This work was performed before the commissioning of digital NR system in Jan. 2013. The MATLAB enhancement method is quite a good technique in the case of static based film neutron radiography, while in neutron imaging (NI) technique, image enhancement and quantitative measurement were efficient by using ImageJ software. The enhanced image quality and quantitative measurements were presented in this work. Copyright © 2014 Elsevier Ltd. All rights reserved.

Orthogonal transformations for change detection, Matlab code (ENVI-like headers)

DEFF Research Database (Denmark)

2007-01-01

Matlab code to do (iteratively reweighted) multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data; accommodates ENVI (like) header files.......Matlab code to do (iteratively reweighted) multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data; accommodates ENVI (like) header files....

ABAQUS2MATLAB: A Novel Tool for Finite Element Post-Processing

DEFF Research Database (Denmark)

Martínez Pañeda, Emilio; Papazafeiropoulos, George; Muniz-Calvente, Miguel

2017-01-01

A novel piece of software is presented to connect Abaqus, a sophisticated finite element package, with Matlab, the most comprehensive program for mathematical analysis. This interface between these well-known codes not only benefits from the image processing and the integrated graph-plotting feat......A novel piece of software is presented to connect Abaqus, a sophisticated finite element package, with Matlab, the most comprehensive program for mathematical analysis. This interface between these well-known codes not only benefits from the image processing and the integrated graph...... to demonstrate its capabilities. The source code, detailed documentation and a large number of tutorials can be freely downloaded from www.abaqus2matlab.com....

A new MATLAB/Simulink model of triple-junction solar cell and MPPT based on artificial neural networks for photovoltaic energy systems

Directory of Open Access Journals (Sweden)

Hegazy Rezk

2015-09-01

Full Text Available This paper presents a new Matlab/Simulink model of a PV module and a maximum power point tracking (MPPT system for high efficiency InGaP/InGaAs/Ge triple-junction solar cell. The proposed technique is based on Artificial Neural Network. The equivalent circuit model of the triple-junction solar cell includes the parameters of each sub-cell. It is also include the effect of the temperature variations on the energy gap of each sub-cell as well as the diode reverse saturation currents. The implementation of a PV model is based on the triple-junction solar cell in the form of masked block in Matlab/Simulink software package that has a user-friendly icon and dialog. It is fast and accurate technique to follow the maximum power point. The simulation results of the proposed MPPT technique are compared with Perturb and Observe MPPT technique. The output power and energy of the proposed technique are higher than that of the Perturb and Observe MPPT technique. The proposed technique increases the output energy per day for a one PV module from 3.37 kW h to 3.75 kW h, i.e. a percentage of 11.28%.

Adaptive antenna array algorithms and their impact on code division ...

African Journals Online (AJOL)

In this paper four each blind adaptive array algorithms are developed, and their performance under different test situations (e.g. A WGN (Additive White Gaussian Noise) channel, and multipath environment) is studied A MATLAB test bed is created to show their performance on these two test situations and an optimum one ...

On flexible CAD of adaptive control and identification algorithms

DEFF Research Database (Denmark)

Christensen, Anders; Ravn, Ole

1988-01-01

a total redesign of the system within each sample. The necessary design parameters are evaluated and a decision vector is defined, from which the identification algorithm can be generated by the program. Using the decision vector, a decision-node tree structure is built up, where the nodes define......SLLAB is a MATLAB-family software package for solving control and identification problems. This paper concerns the planning of a general-purpose subroutine structure for solving identification and adaptive control problems. A general-purpose identification algorithm is suggested, which allows...

Development of Graphical User Interface for Finite Element Analysis of Static Loading of a Column using MATLAB

Directory of Open Access Journals (Sweden)

Moses Omolayo PETINRIN

2010-12-01

Full Text Available In this work, the capability of MATLAB software package to develop graphical user interface (GUI package was demonstrated. A GUI was successfully developed using MATLAB programming language to study the behaviour of a suspended column under uniaxial static loading by solving the numerical model created based on the finite element method (FEM. The comparison between the exact solution from previous researches and the numerical analysis showed good agreement. The column average strain, average stress and average load are equivalent but more accurate to the ones obtained when the whole column is taken as one element (two nodes for one dimensional linear finite element problem. It was established in this work that MATLAB is not only a software package for numerical computation but also for application development.

Wind power limit calculation basedon frequency deviation using Matlab

International Nuclear Information System (INIS)

Santos Fuentefria, Ariel; Salgado Duarte, Yorlandis; MejutoFarray, Davis

2017-01-01

The utilization of the wind energy for the production of electricity it’s a technology that has promoted itself in the last years, like an alternative before the environmental deterioration and the scarcity of the fossil fuels. When the power generation of wind energy is integrated into the electrical power systems, maybe take place problems in the frequency stability due to, mainly, the stochastic characteristic of the wind and the impossibility of the wind power control on behalf of the dispatchers. In this work, is make an analysis of frequency deviation when the wind power generation rise in an isolated electrical power system. This analysis develops in a computerized frame with the construction of an algorithm using Matlab, which allowed to make several simulations in order to obtain the frequency behavior for different loads and wind power conditions. Besides, it was determined the wind power limit for minimum, medium and maximum load. The results show that the greatest values on wind power are obtained in maximum load condition. However, the minimum load condition limit the introduction of wind power into the system. (author)

Efficient MATLAB computations with sparse and factored tensors.

Energy Technology Data Exchange (ETDEWEB)

Bader, Brett William; Kolda, Tamara Gibson (Sandia National Lab, Livermore, CA)

2006-12-01

In this paper, the term tensor refers simply to a multidimensional or N-way array, and we consider how specially structured tensors allow for efficient storage and computation. First, we study sparse tensors, which have the property that the vast majority of the elements are zero. We propose storing sparse tensors using coordinate format and describe the computational efficiency of this scheme for various mathematical operations, including those typical to tensor decomposition algorithms. Second, we study factored tensors, which have the property that they can be assembled from more basic components. We consider two specific types: a Tucker tensor can be expressed as the product of a core tensor (which itself may be dense, sparse, or factored) and a matrix along each mode, and a Kruskal tensor can be expressed as the sum of rank-1 tensors. We are interested in the case where the storage of the components is less than the storage of the full tensor, and we demonstrate that many elementary operations can be computed using only the components. All of the efficiencies described in this paper are implemented in the Tensor Toolbox for MATLAB.

Robust MST-Based Clustering Algorithm.

Science.gov (United States)

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Advanced electric drives analysis, control, and modeling using MATLAB/Simulink

CERN Document Server

Mohan, Ned

2014-01-01

Advanced Electric Drives utilizes a physics-based approach to explain the fundamental concepts of modern electric drive control and its operation under dynamic conditions. Gives readers a "physical" picture of electric machines and drives without resorting to mathematical transformations for easy visualization Confirms the physics-based analysis of electric drives mathematically Provides readers with an analysis of electric machines in a way that can be easily interfaced to common power electronic converters and controlled using any control scheme Makes the MATLAB/Simulink files used in exampl

Hard Ware Implementation of Diamond Search Algorithm for Motion Estimation and Object Tracking

International Nuclear Information System (INIS)

Hashimaa, S.M.; Mahmoud, I.I.; Elazm, A.A.

2009-01-01

Object tracking is very important task in computer vision. Fast search algorithms emerged as important search technique to achieve real time tracking results. To enhance the performance of these algorithms, we advocate the hardware implementation of such algorithms. Diamond search block matching motion estimation has been proposed recently to reduce the complexity of motion estimation. In this paper we selected the diamond search algorithm (DS) for implementation using FPGA. This is due to its fundamental role in all fast search patterns. The proposed architecture is simulated and synthesized using Xilinix and modelsim soft wares. The results agree with the algorithm implementation in Matlab environment.

Continuous Steering Stability Control Based on an Energy-Saving Torque Distribution Algorithm for a Four in-Wheel-Motor Independent-Drive Electric Vehicle

Directory of Open Access Journals (Sweden)

Li Zhai

2018-02-01

Full Text Available In this paper, a continuous steering stability controller based on an energy-saving torque distribution algorithm is proposed for a four in-wheel-motor independent-drive electric vehicle (4MIDEV to improve the energy consumption efficiency while maintaining the stability in steering maneuvers. The controller is designed as a hierarchical structure, including the reference model level, the upper-level controller, and the lower-level controller. The upper-level controller adopts the direct yaw moment control (DYC, which is designed to work continuously during the steering maneuver to better ensure steering stability in extreme situations, rather than working only after the vehicle is judged to be unstable. An adaptive two-hierarchy energy-saving torque distribution algorithm is developed in the lower-level controller with the friction ellipse constraint as a basis for judging whether the algorithm needs to be switched, so as to achieve a more stable and energy-efficient steering operation. The proposed stability controller was validated in a co-simulation of CarSim and Matlab/Simulink. The simulation results under different steering maneuvers indicate that the proposed controller, compared with the conventional servo controller and the ordinary continuous controller, can reduce energy consumption up to 23.68% and improve the vehicle steering stability.

RPI-MATLAB-simulator

DEFF Research Database (Denmark)

Williams, J.; Lu, Y.; Abel, Sarah Maria Niebe

2013-01-01

main goals: 1. Provide an intuitive and easily extendable platform for research and education in multibody dynamics; 2. Maintain an evolving code base of useful algorithms and analysis tools for multibody dynamics problems. Although research often focuses on a specific subset of problems, work too...

Reliability Based Spare Parts Management Using Genetic Algorithm

Directory of Open Access Journals (Sweden)

Rahul Upadhyay

2015-08-01

Full Text Available Effective and efficient inventory management is the key to the economic sustainability of capital intensive modern industries. Inventory grows exponentially with complexity and size of the equipment fleet. Substantial amount of capital is required for maintaining an inventory and therefore its optimization is beneficial for smooth operation of the project at minimum cost of inventory. The size and hence the cost of the inventory is influenced by a large no of factors. This makes the optimization problem complex. This work presents a model to solve the problem of optimization of spare parts inventory. The novelty of this study lies with the fact that the developed method could tackle not only the artificial test case but also a real-world industrial problem. Various investigators developed several methods and semi-analytical tools for obtaining optimum solutions for this problem. In this study non-traditional optimization tool namely genetic algorithms GA are utilized. Apart from this Coxs regression analysis is also used to incorporate the effect of some environmental factors on the demand of spares. It shows the efficacy of the applicability of non-traditional optimization tool like GA to solve these problems. This research illustrates the proposed model with the analysis of data taken from a fleet of dumper operated in a large surface coal mine. The optimum time schedules so suggested by this GA-based model are found to be cost effective. A sensitivity analysis is also conducted for this industrial problem. Objective function is developed and the factors like the effect of season and production pressure overloading towards financial year-ending is included in the equations. Statistical analysis of the collected operational and performance data were carried out with the help of Easy-Fit Ver-5.5.The analysis gives the shape and scale parameter of theoretical Weibull distribution. The Coxs regression coefficient corresponding to excessive loading

Enhancing Student Writing and Computer Programming with LATEX and MATLAB in Multivariable Calculus

Science.gov (United States)

Sullivan, Eric; Melvin, Timothy

2016-01-01

Written communication and computer programming are foundational components of an undergraduate degree in the mathematical sciences. All lower-division mathematics courses at our institution are paired with computer-based writing, coding, and problem-solving activities. In multivariable calculus we utilize MATLAB and LATEX to have students explore…

Detecting variability in MATLAB/Simulink models : an industry-inspired technique and its evaluation

NARCIS (Netherlands)

Schlie, A.; Wille, D.; Schulze, S.; Cleophas, L.G.W.A.; Schaefer, I.

2017-01-01

Model-based languages such as MATLAB/Simulink play an essential role in the model-driven development of software systems. To comply with new requirements, it is common practice to create new variants by copying existing systems and modifying them. Commonly referred to as clone-and-own, severe

Wavelet decomposition based principal component analysis for face recognition using MATLAB

Science.gov (United States)

Sharma, Mahesh Kumar; Sharma, Shashikant; Leeprechanon, Nopbhorn; Ranjan, Aashish

2016-03-01

For the realization of face recognition systems in the static as well as in the real time frame, algorithms such as principal component analysis, independent component analysis, linear discriminate analysis, neural networks and genetic algorithms are used for decades. This paper discusses an approach which is a wavelet decomposition based principal component analysis for face recognition. Principal component analysis is chosen over other algorithms due to its relative simplicity, efficiency, and robustness features. The term face recognition stands for identifying a person from his facial gestures and having resemblance with factor analysis in some sense, i.e. extraction of the principal component of an image. Principal component analysis is subjected to some drawbacks, mainly the poor discriminatory power and the large computational load in finding eigenvectors, in particular. These drawbacks can be greatly reduced by combining both wavelet transform decomposition for feature extraction and principal component analysis for pattern representation and classification together, by analyzing the facial gestures into space and time domain, where, frequency and time are used interchangeably. From the experimental results, it is envisaged that this face recognition method has made a significant percentage improvement in recognition rate as well as having a better computational efficiency.

Abaqus2Matlab: A suitable tool for finite element post-processing

DEFF Research Database (Denmark)

Papazafeiropoulos, George; Muñiz-Calvente, Miguel; Martínez Pañeda, Emilio

2017-01-01

A suitable piece of software is presented to connect Abaqus, a sophisticated finite element package, with Matlab, the most comprehensive program for mathematical analysis. This interface between these well- known codes not only benefits from the image processing and the integrated graph-plotting ......A suitable piece of software is presented to connect Abaqus, a sophisticated finite element package, with Matlab, the most comprehensive program for mathematical analysis. This interface between these well- known codes not only benefits from the image processing and the integrated graph...... crack propagation in structural materials by means of a cohesive zone approach. The source code, detailed documentation and a large number of tutorials can be freely downloaded from www.abaqus2matlab.com ....

An improved cooperative adaptive cruise control (CACC) algorithm considering invalid communication

Science.gov (United States)

Wang, Pangwei; Wang, Yunpeng; Yu, Guizhen; Tang, Tieqiao

2014-05-01

For the Cooperative Adaptive Cruise Control (CACC) Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.

Mathematical Formulation used by MATLAB Code to Convert FTIR Interferograms to Calibrated Spectra

Energy Technology Data Exchange (ETDEWEB)

Armstrong, Derek Elswick [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-07-19

This report discusses the mathematical procedures used to convert raw interferograms from Fourier transform infrared (FTIR) sensors to calibrated spectra. The work discussed in this report was completed as part of the Helios project at Los Alamos National Laboratory. MATLAB code was developed to convert the raw interferograms to calibrated spectra. The report summarizes the developed MATLAB scripts and functions, along with a description of the mathematical methods used by the code. The first step in working with raw interferograms is to convert them to uncalibrated spectra by applying an apodization function to the raw data and then by performing a Fourier transform. The developed MATLAB code also addresses phase error correction by applying the Mertz method. This report provides documentation for the MATLAB scripts.

PreSurgMapp: a MATLAB Toolbox for Presurgical Mapping of Eloquent Functional Areas Based on Task-Related and Resting-State Functional MRI.

Science.gov (United States)

Huang, Huiyuan; Ding, Zhongxiang; Mao, Dewang; Yuan, Jianhua; Zhu, Fangmei; Chen, Shuda; Xu, Yan; Lou, Lin; Feng, Xiaoyan; Qi, Le; Qiu, Wusi; Zhang, Han; Zang, Yu-Feng

2016-10-01

The main goal of brain tumor surgery is to maximize tumor resection while minimizing the risk of irreversible postoperative functional sequelae. Eloquent functional areas should be delineated preoperatively, particularly for patients with tumors near eloquent areas. Functional magnetic resonance imaging (fMRI) is a noninvasive technique that demonstrates great promise for presurgical planning. However, specialized data processing toolkits for presurgical planning remain lacking. Based on several functions in open-source software such as Statistical Parametric Mapping (SPM), Resting-State fMRI Data Analysis Toolkit (REST), Data Processing Assistant for Resting-State fMRI (DPARSF) and Multiple Independent Component Analysis (MICA), here, we introduce an open-source MATLAB toolbox named PreSurgMapp. This toolbox can reveal eloquent areas using comprehensive methods and various complementary fMRI modalities. For example, PreSurgMapp supports both model-based (general linear model, GLM, and seed correlation) and data-driven (independent component analysis, ICA) methods and processes both task-based and resting-state fMRI data. PreSurgMapp is designed for highly automatic and individualized functional mapping with a user-friendly graphical user interface (GUI) for time-saving pipeline processing. For example, sensorimotor and language-related components can be automatically identified without human input interference using an effective, accurate component identification algorithm using discriminability index. All the results generated can be further evaluated and compared by neuro-radiologists or neurosurgeons. This software has substantial value for clinical neuro-radiology and neuro-oncology, including application to patients with low- and high-grade brain tumors and those with epilepsy foci in the dominant language hemisphere who are planning to undergo a temporal lobectomy.

POST II Trajectory Animation Tool Using MATLAB, V1.0

Science.gov (United States)

Raiszadeh, Behzad

2005-01-01

A trajectory animation tool has been developed for accurately depicting position and the attitude of the bodies in flight. The movies generated from This MATLAB based tool serve as an engineering analysis aid to gain further understanding into the dynamic behavior of bodies in flight. This tool has been designed to interface with the output generated from POST II simulations, and is able to animate a single as well as multiple vehicles in flight.

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB.

Directory of Open Access Journals (Sweden)

Lucian A B Purvis

Full Text Available In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from https://github.com/oxsatoolbox/oxsa.

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB.

Science.gov (United States)

Purvis, Lucian A B; Clarke, William T; Biasiolli, Luca; Valkovič, Ladislav; Robson, Matthew D; Rodgers, Christopher T

2017-01-01

In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from https://github.com/oxsatoolbox/oxsa.

Matlab modeling of ITER CODAC

International Nuclear Information System (INIS)

Pangione, L.; Lister, J.B.

2008-01-01

The ITER CODAC (COntrol, Data Access and Communication) conceptual design resulted from 2 years of activity. One result was a proposed functional partitioning of CODAC into different CODAC Systems, each of them partitioned into other CODAC Systems. Considering the large size of this project, simple use of human language assisted by figures would certainly be ineffective in creating an unambiguous description of all interactions and all relations between these Systems. Moreover, the underlying design is resident in the mind of the designers, who must consider all possible situations that could happen to each system. There is therefore a need to model the whole of CODAC with a clear and preferably graphical method, which allows the designers to verify the correctness and the consistency of their project. The aim of this paper is to describe the work started on ITER CODAC modeling using Matlab/Simulink. The main feature of this tool is the possibility of having a simple, graphical, intuitive representation of a complex system and ultimately to run a numerical simulation of it. Using Matlab/Simulink, each CODAC System was represented in a graphical and intuitive form with its relations and interactions through the definition of a small number of simple rules. In a Simulink diagram, each system was represented as a 'black box', both containing, and connected to, a number of other systems. In this way it is possible to move vertically between systems on different levels, to show the relation of membership, or horizontally to analyse the information exchange between systems at the same level. This process can be iterated, starting from a global diagram, in which only CODAC appears with the Plant Systems and the external sites, and going deeper down to the mathematical model of each CODAC system. The Matlab/Simulink features for simulating the whole top diagram encourage us to develop the idea of completing the functionalities of all systems in order to finally have a full

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

Science.gov (United States)

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This

Labbtex: Toolbox para generación de informes en LATEX para Matlab

Directory of Open Access Journals (Sweden)

José Luis Almazán Gárate

2012-10-01

Full Text Available En este artículo se presenta el software desarrollado por el Equipo H3lite dentro del Departamento de Ingeneniería Civil. Transportes de la Escuela de Ingenieros de Caminos, Canales y Puertos de la Universidad Politécnica de Madrid para la generación de informes enLATEX mediante el software Matlab® y la integración en sus rutinas, Labbtex.La librería Labbtex proporciona un marco flexible para mezclar texto y código Matlab® para la generación automática de documentos. Un rchivo fuente simple contiene el texto de documentación y el código Matlab, al correr la aplicación se genera un documento final LATEX que contiene el texto, gráficos y tablas indicados con el formato de un documento LATEX. El código Matlab genera un documento LATEX usando la sintaxis. Así, LATEX (para composición de texto de alta calidad y Matlab® (para cálculo matemático pueden usarse simultáneamente. Esto permite la generación de informes en tiempo real con un uso de recursos mínimo.

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Shepard, A; Bednarz, B [University of Wisconsin, Madison, WI (United States)

2016-06-15

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localized block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA

SU-G-BRA-02: Development of a Learning Based Block Matching Algorithm for Ultrasound Tracking in Radiotherapy

International Nuclear Information System (INIS)

Shepard, A; Bednarz, B

2016-01-01

Purpose: To develop an ultrasound learning-based tracking algorithm with the potential to provide real-time motion traces of anatomy-based fiducials that may aid in the effective delivery of external beam radiation. Methods: The algorithm was developed in Matlab R2015a and consists of two main stages: reference frame selection, and localized block matching. Immediately following frame acquisition, a normalized cross-correlation (NCC) similarity metric is used to determine a reference frame most similar to the current frame from a series of training set images that were acquired during a pretreatment scan. Segmented features in the reference frame provide the basis for the localized block matching to determine the feature locations in the current frame. The boundary points of the reference frame segmentation are used as the initial locations for the block matching and NCC is used to find the most similar block in the current frame. The best matched block locations in the current frame comprise the updated feature boundary. The algorithm was tested using five features from two sets of ultrasound patient data obtained from MICCAI 2014 CLUST. Due to the lack of a training set associated with the image sequences, the first 200 frames of the image sets were considered a valid training set for preliminary testing, and tracking was performed over the remaining frames. Results: Tracking of the five vessel features resulted in an average tracking error of 1.21 mm relative to predefined annotations. The average analysis rate was 15.7 FPS with analysis for one of the two patients reaching real-time speeds. Computations were performed on an i5-3230M at 2.60 GHz. Conclusion: Preliminary tests show tracking errors comparable with similar algorithms at close to real-time speeds. Extension of the work onto a GPU platform has the potential to achieve real-time performance, making tracking for therapy applications a feasible option. This work is partially funded by NIH grant R01CA

A recursive algorithm for computing the inverse of the Vandermonde matrix

Directory of Open Access Journals (Sweden)

Youness Aliyari Ghassabeh

2016-12-01

Full Text Available The inverse of a Vandermonde matrix has been used for signal processing, polynomial interpolation, curve fitting, wireless communication, and system identification. In this paper, we propose a novel fast recursive algorithm to compute the inverse of a Vandermonde matrix. The algorithm computes the inverse of a higher order Vandermonde matrix using the available lower order inverse matrix with a computational cost of $ O(n^2 $. The proposed algorithm is given in a matrix form, which makes it appropriate for hardware implementation. The running time of the proposed algorithm to find the inverse of a Vandermonde matrix using a lower order Vandermonde matrix is compared with the running time of the matrix inversion function implemented in MATLAB.

New Algorithm for Evaluating the Green Supply Chain Performance in an Uncertain Environment

Directory of Open Access Journals (Sweden)

Pan Liu

2016-09-01

Full Text Available An effective green supply chain (GSC can help an enterprise obtain more benefits and reduce costs. Therefore, developing an effective evaluation method for GSC performance evaluation is becoming increasingly important. In this study, the advantages and disadvantages of the current performance evaluations and algorithms for GSC performance evaluations were discussed and evaluated. Based on these findings, an improved five-dimensional balanced scorecard was proposed in which the green performance indicators were revised to facilitate their measurement. A model based on Rough Set theory, the Genetic Algorithm, and the Levenberg Marquardt Back Propagation (LMBP neural network algorithm was proposed. Next, using Matlab, the Rosetta tool, and the practical data of company F, a case study was conducted. The results indicate that the proposed model has a high convergence speed and an accurate prediction ability. The credibility and effectiveness of the proposed model was validated. In comparison with the normal Back Propagation neural network algorithm and the LMBP neural network algorithm, the proposed model has greater credibility and effectiveness. In practice, this method provides a more suitable indicator system and algorithm for enterprises to be able to implement GSC performance evaluations in an uncertain environment. Academically, the proposed method addresses the lack of a theoretical basis for GSC performance evaluation, thus representing a new development in GSC performance evaluation theory.

Matlab Geochemistry: An open source geochemistry solver based on MRST

Science.gov (United States)

McNeece, C. J.; Raynaud, X.; Nilsen, H.; Hesse, M. A.

2017-12-01

The study of geological systems often requires the solution of complex geochemical relations. To address this need we present an open source geochemical solver based on the Matlab Reservoir Simulation Toolbox (MRST) developed by SINTEF. The implementation supports non-isothermal multicomponent aqueous complexation, surface complexation, ion exchange, and dissolution/precipitation reactions. The suite of tools available in MRST allows for rapid model development, in particular the incorporation of geochemical calculations into transport simulations of multiple phases, complex domain geometry and geomechanics. Different numerical schemes and additional physics can be easily incorporated into the existing tools through the object-oriented framework employed by MRST. The solver leverages the automatic differentiation tools available in MRST to solve arbitrarily complex geochemical systems with any choice of species or element concentration as input. Four mathematical approaches enable the solver to be quite robust: 1) the choice of chemical elements as the basis components makes all entries in the composition matrix positive thus preserving convexity, 2) a log variable transformation is used which transfers the nonlinearity to the convex composition matrix, 3) a priori bounds on variables are calculated from the structure of the problem, constraining Netwon's path and 4) an initial guess is calculated implicitly by sequentially adding model complexity. As a benchmark we compare the model to experimental and semi-analytic solutions of the coupled salinity-acidity transport system. Together with the reservoir simulation capabilities of MRST the solver offers a promising tool for geochemical simulations in reservoir domains for applications in a diversity of fields from enhanced oil recovery to radionuclide storage.

Using health and demographic surveillance for the early detection of cholera outbreaks: analysis of community- and hospital-based data from Matlab, Bangladesh.

Science.gov (United States)

Saulnier, Dell D; Persson, Lars-Åke; Streatfield, Peter Kim; Faruque, A S G; Rahman, Anisur

2016-01-01

Cholera outbreaks are a continuing problem in Bangladesh, and the timely detection of an outbreak is important for reducing morbidity and mortality. In Matlab, the ongoing Health and Demographic Surveillance System (HDSS) data records symptoms of diarrhea in children under the age of 5 years at the community level. Cholera surveillance in Matlab currently uses hospital-based data. The objective of this study is to determine whether increases in cholera in Matlab can be detected earlier by using HDSS diarrhea symptom data in a syndromic surveillance analysis, when compared to hospital admissions for cholera. HDSS diarrhea symptom data and hospital admissions for cholera in children under 5 years of age over a 2-year period were analyzed with the syndromic surveillance statistical program EARS (Early Aberration Reporting System). Dates when significant increases in either symptoms or cholera cases occurred were compared to one another. The analysis revealed that there were 43 days over 16 months when the cholera cases or diarrhea symptoms increased significantly. There were 8 months when both data sets detected days with significant increases. In 5 of the 8 months, increases in diarrheal symptoms occurred before increases of cholera cases. The increases in symptoms occurred between 1 and 15 days before the increases in cholera cases. The results suggest that the HDSS survey data may be able to detect an increase in cholera before an increase in hospital admissions is seen. However, there was no direct link between diarrheal symptom increases and cholera cases, and this, as well as other methodological weaknesses, should be taken into consideration.

A primal-dual exterior point algorithm for linear programming problems

Directory of Open Access Journals (Sweden)

Samaras Nikolaos

2009-01-01

Full Text Available The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study has been carried out, using randomly generated sparse optimal linear problems, to compare its computational efficiency with the Primal Simplex algorithm and also with MATLAB's Interior Point Method implementation. The algorithm appears to be very promising since it clearly shows its superiority to the Primal Simplex algorithm as well as its robustness over the IPM algorithm.

Estimation of biometric parameters from cattle rump using free-hand scanning and a 3D data processing algorithm

OpenAIRE

Viana, Joao; Hinduja, Srichand; Da Silva Bartolo, Paulo Jorge

2016-01-01

The quantity and quality of phenotypic data recovered from farm animals became a bottleneck for breeding programmes, and new tools are required to overcome this problem. This study evaluated the use of a portable structured light scanner and a 3D modelling to recover biometric information of the rump region in cattle. Virtual 3D models were created based on coordinates extracted from the points-cloud obtained through reverse engineering. A MATLAB algorithm was implemented to identify referenc...

Seizure detection algorithms based on EMG signals

DEFF Research Database (Denmark)

Conradsen, Isa

Background: the currently used non-invasive seizure detection methods are not reliable. Muscle fibers are directly connected to the nerves, whereby electric signals are generated during activity. Therefore, an alarm system on electromyography (EMG) signals is a theoretical possibility. Objective...... on the amplitude of the signal. The other algorithm was based on information of the signal in the frequency domain, and it focused on synchronisation of the electrical activity in a single muscle during the seizure. Results: The amplitude-based algorithm reliably detected seizures in 2 of the patients, while...... the frequency-based algorithm was efficient for detecting the seizures in the third patient. Conclusion: Our results suggest that EMG signals could be used to develop an automatic seizuredetection system. However, different patients might require different types of algorithms /approaches....

Verification-Based Interval-Passing Algorithm for Compressed Sensing

OpenAIRE

Wu, Xiaofu; Yang, Zhen

2013-01-01

We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation resul...

Gradient Evolution-based Support Vector Machine Algorithm for Classification

Science.gov (United States)

Zulvia, Ferani E.; Kuo, R. J.

2018-03-01

This paper proposes a classification algorithm based on a support vector machine (SVM) and gradient evolution (GE) algorithms. SVM algorithm has been widely used in classification. However, its result is significantly influenced by the parameters. Therefore, this paper aims to propose an improvement of SVM algorithm which can find the best SVMs’ parameters automatically. The proposed algorithm employs a GE algorithm to automatically determine the SVMs’ parameters. The GE algorithm takes a role as a global optimizer in finding the best parameter which will be used by SVM algorithm. The proposed GE-SVM algorithm is verified using some benchmark datasets and compared with other metaheuristic-based SVM algorithms. The experimental results show that the proposed GE-SVM algorithm obtains better results than other algorithms tested in this paper.

A Trust-region-based Sequential Quadratic Programming Algorithm

DEFF Research Database (Denmark)

Henriksen, Lars Christian; Poulsen, Niels Kjølstad

This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints.......This technical note documents the trust-region-based sequential quadratic programming algorithm used in other works by the authors. The algorithm seeks to minimize a convex nonlinear cost function subject to linear inequalty constraints and nonlinear equality constraints....

Powertrain Matching and Optimization of Dual-Motor Hybrid Driving System for Electric Vehicle Based on Quantum Genetic Intelligent Algorithm

Directory of Open Access Journals (Sweden)

Yong Wang

2014-01-01

Full Text Available In order to increase the driving range and improve the overall performance of all-electric vehicles, a new dual-motor hybrid driving system with two power sources was proposed. This system achieved torque-speed coupling between the two power sources and greatly improved the high performance working range of the motors; at the same time, continuously variable transmission (CVT was achieved to efficiently increase the driving range. The power system parameters were determined using the “global optimization method”; thus, the vehicle’s dynamics and economy were used as the optimization indexes. Based on preliminary matches, quantum genetic algorithm was introduced to optimize the matching in the dual-motor hybrid power system. Backward simulation was performed on the combined simulation platform of Matlab/Simulink and AVL-Cruise to optimize, simulate, and verify the system parameters of the transmission system. Results showed that quantum genetic algorithms exhibited good global optimization capability and convergence in dealing with multiobjective and multiparameter optimization. The dual-motor hybrid-driving system for electric cars satisfied the dynamic performance and economy requirements of design, efficiently increasing the driving range of the car, having high performance, and reducing energy consumption of 15.6% compared with the conventional electric vehicle with single-speed reducers.

Fission gas bubble identification using MATLAB's image processing toolbox

Energy Technology Data Exchange (ETDEWEB)

Collette, R. [Colorado School of Mines, Nuclear Science and Engineering Program, 1500 Illinois St, Golden, CO 80401 (United States); King, J., E-mail: kingjc@mines.edu [Colorado School of Mines, Nuclear Science and Engineering Program, 1500 Illinois St, Golden, CO 80401 (United States); Keiser, D.; Miller, B.; Madden, J.; Schulthess, J. [Nuclear Fuels and Materials Division, Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-6188 (United States)

2016-08-15

Automated image processing routines have the potential to aid in the fuel performance evaluation process by eliminating bias in human judgment that may vary from person-to-person or sample-to-sample. This study presents several MATLAB based image analysis routines designed for fission gas void identification in post-irradiation examination of uranium molybdenum (U–Mo) monolithic-type plate fuels. Frequency domain filtration, enlisted as a pre-processing technique, can eliminate artifacts from the image without compromising the critical features of interest. This process is coupled with a bilateral filter, an edge-preserving noise removal technique aimed at preparing the image for optimal segmentation. Adaptive thresholding proved to be the most consistent gray-level feature segmentation technique for U–Mo fuel microstructures. The Sauvola adaptive threshold technique segments the image based on histogram weighting factors in stable contrast regions and local statistics in variable contrast regions. Once all processing is complete, the algorithm outputs the total fission gas void count, the mean void size, and the average porosity. The final results demonstrate an ability to extract fission gas void morphological data faster, more consistently, and at least as accurately as manual segmentation methods. - Highlights: •Automated image processing can aid in the fuel qualification process. •Routines are developed to characterize fission gas bubbles in irradiated U–Mo fuel. •Frequency domain filtration effectively eliminates FIB curtaining artifacts. •Adaptive thresholding proved to be the most accurate segmentation method. •The techniques established are ready to be applied to large scale data extraction testing.

Data analysis algorithms for flaw sizing based on eddy current rotating probe examination of steam generator tubes

International Nuclear Information System (INIS)

Bakhtiari, S.; Elmer, T.W.

2009-01-01

Computer-aided data analysis tools can help improve the efficiency and reliability of flaw sizing based on nondestructive examination data. They can further help produce more consistent results, which is important for both in-service inspection applications and for engineering assessments associated with steam generator tube integrity. Results of recent investigations at Argonne on the development of various algorithms for sizing of flaws in steam generator tubes based on eddy current rotating probe data are presented. The research was carried out as part of the activities under the International Steam Generator Tube Integrity Program (ISG-TIP) sponsored by the U.S. Nuclear Regulatory Commission. A computer-aided data analysis tool has been developed for off-line processing of eddy current inspection data. The main objectives of the work have been to a) allow all data processing stages to be performed under the same user interface, b) simplify modification and testing of signal processing and data analysis scripts, and c) allow independent evaluation of viable flaw sizing algorithms. The focus of most recent studies at Argonne has been on the processing of data acquired with the +Point probe, which is one of the more widely used eddy current rotating probes for steam generator tube examinations in the U.S. The probe employs a directional surface riding differential coil, which helps reduce the influence of tubing artifacts and in turn helps improve the signal-to-noise ratio. Various algorithms developed under the MATLAB environment for the conversion, segmentation, calibration, and analysis of data have been consolidated within a single user interface. Data acquired with a number of standard eddy current test equipment are automatically recognized and converted to a standard format for further processing. Because of its modular structure, the graphical user interface allows user-developed routines to be easily incorporated, modified, and tested independent of the

Gravitation field algorithm and its application in gene cluster

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Zheng Ming

2010-09-01

Full Text Available Abstract Background Searching optima is one of the most challenging tasks in clustering genes from available experimental data or given functions. SA, GA, PSO and other similar efficient global optimization methods are used by biotechnologists. All these algorithms are based on the imitation of natural phenomena. Results This paper proposes a novel searching optimization algorithm called Gravitation Field Algorithm (GFA which is derived from the famous astronomy theory Solar Nebular Disk Model (SNDM of planetary formation. GFA simulates the Gravitation field and outperforms GA and SA in some multimodal functions optimization problem. And GFA also can be used in the forms of unimodal functions. GFA clusters the dataset well from the Gene Expression Omnibus. Conclusions The mathematical proof demonstrates that GFA could be convergent in the global optimum by probability 1 in three conditions for one independent variable mass functions. In addition to these results, the fundamental optimization concept in this paper is used to analyze how SA and GA affect the global search and the inherent defects in SA and GA. Some results and source code (in Matlab are publicly available at http://ccst.jlu.edu.cn/CSBG/GFA.

Change detection algorithms for surveillance in visual iot: a comparative study

International Nuclear Information System (INIS)

Akram, B.A.; Zafar, A.; Akbar, A.H.; Chaudhry, A.

2018-01-01

The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule’s Coefficient) and JC (Jaccard’s Coefficient), execution time and memory consumption. Experimental results showed that Kapur’s algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes. (author)

Advanced processing and simulation of MRS data using the FID appliance (FID-A)-An open source, MATLAB-based toolkit.

Science.gov (United States)

Simpson, Robin; Devenyi, Gabriel A; Jezzard, Peter; Hennessy, T Jay; Near, Jamie

2017-01-01

To introduce a new toolkit for simulation and processing of magnetic resonance spectroscopy (MRS) data, and to demonstrate some of its novel features. The FID appliance (FID-A) is an open-source, MATLAB-based software toolkit for simulation and processing of MRS data. The software is designed specifically for processing data with multiple dimensions (eg, multiple radiofrequency channels, averages, spectral editing dimensions). It is equipped with functions for importing data in the formats of most major MRI vendors (eg, Siemens, Philips, GE, Agilent) and for exporting data into the formats of several common processing software packages (eg, LCModel, jMRUI, Tarquin). This paper introduces the FID-A software toolkit and uses examples to demonstrate its novel features, namely 1) the use of a spectral registration algorithm to carry out useful processing routines automatically, 2) automatic detection and removal of motion-corrupted scans, and 3) the ability to perform several major aspects of the MRS computational workflow from a single piece of software. This latter feature is illustrated through both high-level processing of in vivo GABA-edited MEGA-PRESS MRS data, as well as detailed quantum mechanical simulations to generate an accurate LCModel basis set for analysis of the same data. All of the described processing steps resulted in a marked improvement in spectral quality compared with unprocessed data. Fitting of MEGA-PRESS data using a customized basis set resulted in improved fitting accuracy compared with a generic MEGA-PRESS basis set. The FID-A software toolkit enables high-level processing of MRS data and accurate simulation of in vivo MRS experiments. Magn Reson Med 77:23-33, 2017. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Design of SVC Controller Based on Improved Biogeography-Based Optimization Algorithm

Directory of Open Access Journals (Sweden)

Feifei Dong

2014-01-01

Full Text Available Considering that common subsynchronous resonance controllers cannot adapt to the characteristics of the time-varying and nonlinear behavior of a power system, the cosine migration model, the improved migration operator, and the mutative scale of chaos and Cauchy mutation strategy are introduced into an improved biogeography-based optimization (IBBO algorithm in order to design an optimal subsynchronous damping controller based on the mechanism of suppressing SSR by static var compensator (SVC. The effectiveness of the improved controller is verified by eigenvalue analysis and electromagnetic simulations. The simulation results of Jinjie plant indicate that the subsynchronous damping controller optimized by the IBBO algorithm can remarkably improve the damping of torsional modes and thus effectively depress SSR, and ensure the safety and stability of units and power grid operation. Moreover, the IBBO algorithm has the merits of a faster searching speed and higher searching accuracy in seeking the optimal control parameters over traditional algorithms, such as BBO algorithm, PSO algorithm, and GA algorithm.

A computational environment for long-term multi-feature and multi-algorithm seizure prediction.

Science.gov (United States)

Teixeira, C A; Direito, B; Costa, R P; Valderrama, M; Feldwisch-Drentrup, H; Nikolopoulos, S; Le Van Quyen, M; Schelter, B; Dourado, A

2010-01-01

The daily life of epilepsy patients is constrained by the possibility of occurrence of seizures. Until now, seizures cannot be predicted with sufficient sensitivity and specificity. Most of the seizure prediction studies have been focused on a small number of patients, and frequently assuming unrealistic hypothesis. This paper adopts the view that for an appropriate development of reliable predictors one should consider long-term recordings and several features and algorithms integrated in one software tool. A computational environment, based on Matlab (®), is presented, aiming to be an innovative tool for seizure prediction. It results from the need of a powerful and flexible tool for long-term EEG/ECG analysis by multiple features and algorithms. After being extracted, features can be subjected to several reduction and selection methods, and then used for prediction. The predictions can be conducted based on optimized thresholds or by applying computational intelligence methods. One important aspect is the integrated evaluation of the seizure prediction characteristic of the developed predictors.

EEGVIS: A MATLAB toolbox for browsing, exploring, and viewing large datasets

Directory of Open Access Journals (Sweden)

Kay A Robbins

2012-05-01

Full Text Available Recent advances in data monitoring and sensor technology have accelerated the acquisition of very large data sets. Streaming data sets from instrumentation such as multi-channel EEG recording usually must undergo substantial pre-processing and artifact removal. Even when using automated procedures, most scientists engage in laborious manual examination and processing to assure high quality data and to indentify interesting or problematic data segments. Researchers also do not have a convenient method of method of visually assessing the effects of applying any stage in a processing pipeline. EEGVIS is a MATLAB toolbox that allows users to quickly explore multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. Customizable summary views reveal potentially interesting sections of data, which users can explore further by clicking to examine using detailed viewing components. The viewer and a companion browser are built on our MoBBED framework, which has a library of modular viewing components that can be mixed and matched to best reveal structure. Users can easily create new viewers for their specific data without any programming during the exploration process. These viewers automatically support pan, zoom, resizing of individual components, and cursor exploration. The toolbox can be used directly in MATLAB at any stage in a processing pipeline, as a plug in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license at http://visual.cs.utsa.edu/ eegvis.

EEGVIS: A MATLAB Toolbox for Browsing, Exploring, and Viewing Large Datasets.

Science.gov (United States)

Robbins, Kay A

2012-01-01

Recent advances in data monitoring and sensor technology have accelerated the acquisition of very large data sets. Streaming data sets from instrumentation such as multi-channel EEG recording usually must undergo substantial pre-processing and artifact removal. Even when using automated procedures, most scientists engage in laborious manual examination and processing to assure high quality data and to indentify interesting or problematic data segments. Researchers also do not have a convenient method of method of visually assessing the effects of applying any stage in a processing pipeline. EEGVIS is a MATLAB toolbox that allows users to quickly explore multi-channel EEG and other large array-based data sets using multi-scale drill-down techniques. Customizable summary views reveal potentially interesting sections of data, which users can explore further by clicking to examine using detailed viewing components. The viewer and a companion browser are built on our MoBBED framework, which has a library of modular viewing components that can be mixed and matched to best reveal structure. Users can easily create new viewers for their specific data without any programming during the exploration process. These viewers automatically support pan, zoom, resizing of individual components, and cursor exploration. The toolbox can be used directly in MATLAB at any stage in a processing pipeline, as a plug-in for EEGLAB, or as a standalone precompiled application without MATLAB running. EEGVIS and its supporting packages are freely available under the GNU general public license at http://visual.cs.utsa.edu/eegvis.

Simple sorting algorithm test based on CUDA

OpenAIRE

Meng, Hongyu; Guo, Fangjin

2015-01-01

With the development of computing technology, CUDA has become a very important tool. In computer programming, sorting algorithm is widely used. There are many simple sorting algorithms such as enumeration sort, bubble sort and merge sort. In this paper, we test some simple sorting algorithm based on CUDA and draw some useful conclusions.

Generation of synthetic gamma spectra with MATLAB

International Nuclear Information System (INIS)

Palmerio, Julian J.; Coppo, Anibal D.

2009-01-01

Objectives: The aim of this work is the simulation of gamma spectra using the MATLAB program to generate the calibration curves in efficiency, which will be used to measure radioactive waste in drums. They are necessary for the proper characterization of these drums. A Monte Carlo simulation was basically developed with the random number generator Mersenne Twister and nuclear data obtained from NIST. This paper shows the results obtained and difficulties encountered until today. The physical correction of the simulated spectra has been the only aspect we have been working, up to this moment. Procedures: A simplified representation of the 'Laboratorio de Verificacion y Control de la Calidad' was chosen. Drums with cemented liquid waste are routinely measured in this laboratory. The commercial program MCNP was also used to get a valid reference in the field of simulation of spectra. We analyzed the spectra obtained by MATLAB in the light of classical literature photon detection and the spectrum obtained by MCNP. Conclusions: Currently the program developed seems adequate to simulate a measurement in the 'Laboratorio de Verificacion y Control de la Calidad'. The spectra obtained by MATLAB seem to physically represent what is observed in real spectra. However, it is a slow program. The current development efforts are directed to improve the speed of simulation. An alternative is to use the CUDA language for NVIDIA video cards to parallelized the simulation. An adequate simulation of the electronic measuring chain is also needed to obtain better representations of the shapes of the peaks. (author)

SIFT based algorithm for point feature tracking

Directory of Open Access Journals (Sweden)

Adrian BURLACU

2007-12-01

Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.

The Dynamo package for tomography and subtomogram averaging: components for MATLAB, GPU computing and EC2 Amazon Web Services.

Science.gov (United States)

Castaño-Díez, Daniel

2017-06-01

Dynamo is a package for the processing of tomographic data. As a tool for subtomogram averaging, it includes different alignment and classification strategies. Furthermore, its data-management module allows experiments to be organized in groups of tomograms, while offering specialized three-dimensional tomographic browsers that facilitate visualization, location of regions of interest, modelling and particle extraction in complex geometries. Here, a technical description of the package is presented, focusing on its diverse strategies for optimizing computing performance. Dynamo is built upon mbtools (middle layer toolbox), a general-purpose MATLAB library for object-oriented scientific programming specifically developed to underpin Dynamo but usable as an independent tool. Its structure intertwines a flexible MATLAB codebase with precompiled C++ functions that carry the burden of numerically intensive operations. The package can be delivered as a precompiled standalone ready for execution without a MATLAB license. Multicore parallelization on a single node is directly inherited from the high-level parallelization engine provided for MATLAB, automatically imparting a balanced workload among the threads in computationally intense tasks such as alignment and classification, but also in logistic-oriented tasks such as tomogram binning and particle extraction. Dynamo supports the use of graphical processing units (GPUs), yielding considerable speedup factors both for native Dynamo procedures (such as the numerically intensive subtomogram alignment) and procedures defined by the user through its MATLAB-based GPU library for three-dimensional operations. Cloud-based virtual computing environments supplied with a pre-installed version of Dynamo can be publicly accessed through the Amazon Elastic Compute Cloud (EC2), enabling users to rent GPU computing time on a pay-as-you-go basis, thus avoiding upfront investments in hardware and longterm software maintenance.

Real-Coded Quantum-Inspired Genetic Algorithm-Based BP Neural Network Algorithm

Directory of Open Access Journals (Sweden)

Jianyong Liu

2015-01-01

Full Text Available The method that the real-coded quantum-inspired genetic algorithm (RQGA used to optimize the weights and threshold of BP neural network is proposed to overcome the defect that the gradient descent method makes the algorithm easily fall into local optimal value in the learning process. Quantum genetic algorithm (QGA is with good directional global optimization ability, but the conventional QGA is based on binary coding; the speed of calculation is reduced by the coding and decoding processes. So, RQGA is introduced to explore the search space, and the improved varied learning rate is adopted to train the BP neural network. Simulation test shows that the proposed algorithm is effective to rapidly converge to the solution conformed to constraint conditions.

Integration of MATLAB Simulink(Registered Trademark) Models with the Vertical Motion Simulator

Science.gov (United States)

Lewis, Emily K.; Vuong, Nghia D.

2012-01-01

This paper describes the integration of MATLAB Simulink(Registered TradeMark) models into the Vertical Motion Simulator (VMS) at NASA Ames Research Center. The VMS is a high-fidelity, large motion flight simulator that is capable of simulating a variety of aerospace vehicles. Integrating MATLAB Simulink models into the VMS needed to retain the development flexibility of the MATLAB environment and allow rapid deployment of model changes. The process developed at the VMS was used successfully in a number of recent simulation experiments. This accomplishment demonstrated that the model integrity was preserved, while working within the hard real-time run environment of the VMS architecture, and maintaining the unique flexibility of the VMS to meet diverse research requirements.

Eigenvalue Decomposition-Based Modified Newton Algorithm

Directory of Open Access Journals (Sweden)

Wen-jun Wang

2013-01-01

Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.

A Novel Cloud-Based Platform for Implementation of Oblivious Power Routing for Clusters of Microgrids

DEFF Research Database (Denmark)

Broojeni, Kianoosh; Amini, M. Hadi; Nejadpak, Arash

2016-01-01

is verified by MATLAB simulation. We also present a comprehensive cloud-based platform for further implementation of the proposed algorithm on the OPAL-RT real-time digital simulation system. The communication paths between the microgrids and the cloud environment can be emulated by OMNeT++....

Optimization Shape of Variable Capacitance Micromotor Using Differential Evolution Algorithm

Directory of Open Access Journals (Sweden)

A. Ketabi

2010-01-01

Full Text Available A new method for optimum shape design of variable capacitance micromotor (VCM using Differential Evolution (DE, a stochastic search algorithm, is presented. In this optimization exercise, the objective function aims to maximize torque value and minimize the torque ripple, where the geometric parameters are considered to be the variables. The optimization process is carried out using a combination of DE algorithm and FEM analysis. Fitness value is calculated by FEM analysis using COMSOL3.4, and the DE algorithm is realized by MATLAB7.4. The proposed method is applied to a VCM with 8 poles at the stator and 6 poles at the rotor. The results show that the optimized micromotor using DE algorithm had higher torque value and lower torque ripple, indicating the validity of this methodology for VCM design.

Novel density-based and hierarchical density-based clustering algorithms for uncertain data.

Science.gov (United States)

Zhang, Xianchao; Liu, Han; Zhang, Xiaotong

2017-09-01

Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them density-based techniques seem promising for handling data uncertainty. However, some issues like losing uncertain information, high time complexity and nonadaptive threshold have not been addressed well in the previous density-based algorithm FDBSCAN and hierarchical density-based algorithm FOPTICS. In this paper, we firstly propose a novel density-based algorithm PDBSCAN, which improves the previous FDBSCAN from the following aspects: (1) it employs a more accurate method to compute the probability that the distance between two uncertain objects is less than or equal to a boundary value, instead of the sampling-based method in FDBSCAN; (2) it introduces new definitions of probability neighborhood, support degree, core object probability, direct reachability probability, thus reducing the complexity and solving the issue of nonadaptive threshold (for core object judgement) in FDBSCAN. Then, we modify the algorithm PDBSCAN to an improved version (PDBSCANi), by using a better cluster assignment strategy to ensure that every object will be assigned to the most appropriate cluster, thus solving the issue of nonadaptive threshold (for direct density reachability judgement) in FDBSCAN. Furthermore, as PDBSCAN and PDBSCANi have difficulties for clustering uncertain data with non-uniform cluster density, we propose a novel hierarchical density-based algorithm POPTICS by extending the definitions of PDBSCAN, adding new definitions of fuzzy core distance and fuzzy reachability distance, and employing a new clustering framework. POPTICS can reveal the cluster structures of the datasets with different local densities in different regions better than PDBSCAN and PDBSCANi, and it addresses the issues in FOPTICS. Experimental results demonstrate the superiority of our proposed algorithms over the existing

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems.

Science.gov (United States)

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K

2017-12-19

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

A Matlab-based finite-difference solver for the Poisson problem with mixed Dirichlet-Neumann boundary conditions

Science.gov (United States)

Reimer, Ashton S.; Cheviakov, Alexei F.

2013-03-01

A Matlab-based finite-difference numerical solver for the Poisson equation for a rectangle and a disk in two dimensions, and a spherical domain in three dimensions, is presented. The solver is optimized for handling an arbitrary combination of Dirichlet and Neumann boundary conditions, and allows for full user control of mesh refinement. The solver routines utilize effective and parallelized sparse vector and matrix operations. Computations exhibit high speeds, numerical stability with respect to mesh size and mesh refinement, and acceptable error values even on desktop computers. Catalogue identifier: AENQ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENQ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3.0 No. of lines in distributed program, including test data, etc.: 102793 No. of bytes in distributed program, including test data, etc.: 369378 Distribution format: tar.gz Programming language: Matlab 2010a. Computer: PC, Macintosh. Operating system: Windows, OSX, Linux. RAM: 8 GB (8, 589, 934, 592 bytes) Classification: 4.3. Nature of problem: To solve the Poisson problem in a standard domain with “patchy surface”-type (strongly heterogeneous) Neumann/Dirichlet boundary conditions. Solution method: Finite difference with mesh refinement. Restrictions: Spherical domain in 3D; rectangular domain or a disk in 2D. Unusual features: Choice between mldivide/iterative solver for the solution of large system of linear algebraic equations that arise. Full user control of Neumann/Dirichlet boundary conditions and mesh refinement. Running time: Depending on the number of points taken and the geometry of the domain, the routine may take from less than a second to several hours to execute.

Integration of Modeling in Solidworks and Matlab/Simulink Environments

Directory of Open Access Journals (Sweden)

Cekus Dawid

2014-03-01

Full Text Available W pracy opisano tok postepowania podczas budowy modeli symulacyjnych z wykorzystaniem programu SolidWorks i Matlab/Simulink. Tworzenie modelu symulacyjnego przebiega etapami, to znaczy najpierw opracowywany jest model geometryczny w programie SolidWorks, nastepnie dzieki mozliwosci wymiany danych, model CAD jest implementowany w srodowisku obliczeniowym Matlab/Simulink. Modele SimMechanics pozwalaja na sledzenie wielu parametrów, np. trajektorii, predkosci, czy przyspieszen dowolnych elementów układu złozonego. W pracy, jako przykłady modeli symulacyjnych opracowanych zgodnie z zaprezentowana metoda, pokazano modele laboratoryjnego zurawia samochodowego oraz zurawia lesnego. Modele te umozliwiaja wizualizacje zadanego - za pomoca wymuszen kinematycznych - cyklu pracy.

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

A novel proton exchange membrane fuel cell based power conversion system for telecom supply with genetic algorithm assisted intelligent interfacing converter

International Nuclear Information System (INIS)

Kaur, Rajvir; Krishnasamy, Vijayakumar; Muthusamy, Kaleeswari; Chinnamuthan, Periasamy

2017-01-01

Highlights: • Proton exchange membrane fuel cell based telecom tower supply is proposed. • The use of diesel generator is eliminated and battery size is reduced. • Boost converter based intelligent interfacing unit is implemented. • The genetic algorithm assisted controller is proposed for effective interfacing. • The controller is robust against input and output disturbance rejection. - Abstract: This paper presents the fuel cell based simple electric energy conversion system for supplying the telecommunication towers to reduce the operation and maintenance cost of telecom companies. The telecom industry is at the boom and is penetrating deep into remote rural areas having unreliable or no grid supply. The telecom industry is getting heavily dependent on a diesel generator set and battery bank as a backup for continuously supplying a base transceiver station of telecom towers. This excessive usage of backup supply resulted in increased operational expenditure, the unreliability of power supply and had become a threat to the environment. A significant development and concern of clean energy sources, proton exchange membrane fuel cell based supply for base transceiver station is proposed with intelligent interfacing unit. The necessity of the battery bank capacity is significantly reduced as compared with the earlier solutions. Further, a simple closed loop and genetic algorithm assisted controller is proposed for intelligent interfacing unit which consists of power electronic boost converter for power conditioning. The proposed genetic algorithm assisted controller would ensure the tight voltage regulation at the DC distribution bus of the base transceiver station. Also, it will provide the robust performance of the base transceiver station under telecom load variation and proton exchange membrane fuel cell output voltage fluctuations. The complete electric energy conversion system along with telecom loads is simulated in MATLAB/Simulink platform and

Control-oriented Automatic System for Transport Analysis (ASTRA)-Matlab integration for Tokamaks

International Nuclear Information System (INIS)

Sevillano, M.G.; Garrido, I.; Garrido, A.J.

2011-01-01

The exponential growth in energy consumption has led to a renewed interest in the development of alternatives to fossil fuels. Between the unconventional resources that may help to meet this energy demand, nuclear fusion has arisen as a promising source, which has given way to an unprecedented interest in solving the different control problems existing in nuclear fusion reactors such as Tokamaks. The aim of this manuscript is to show how one of the most popular codes used to simulate the performance of Tokamaks, the Automatic System For Transport Analysis (ASTRA) code, can be integrated into the Matlab-Simulink tool in order to make easier and more comfortable the development of suitable controllers for Tokamaks. As a demonstrative case study to show the feasibility and the goodness of the proposed ASTRA-Matlab integration, a modified anti-windup Proportional Integral Derivative (PID)-based controller for the loop voltage of a Tokamak has been implemented. The integration achieved represents an original and innovative work in the Tokamak control area and it provides new possibilities for the development and application of advanced control schemes to the standardized and widely extended ASTRA transport code for Tokamaks. -- Highlights: → The paper presents a useful tool for rapid prototyping of different solutions to deal with the control problems arising in Tokamaks. → The proposed tool embeds the standardized Automatic System For Transport Analysis (ASTRA) code for Tokamaks within the well-known Matlab-Simulink software. → This allows testing and combining diverse control schemes in a unified way considering the ASTRA as the plant of the system. → A demonstrative Proportional Integral Derivative (PID)-based case study is provided to show the feasibility and capabilities of the proposed integration.

FIT3D toolbox: multiple view geometry and 3D reconstruction for Matlab

NARCIS (Netherlands)

Esteban, I.; Dijk, J.; Groen, F.

2010-01-01

FIT3D is a Toolbox built for Matlab that aims at unifying and distributing a set of tools that will allow the researcher to obtain a complete 3D model from a set of calibrated images. In this paper we motivate and present the structure of the toolbox in a tutorial and example based approach. Given

A Distance-Adaptive Refueling Recommendation Algorithm for Self-Driving Travel

Directory of Open Access Journals (Sweden)

Quanli Xu

2018-03-01

Full Text Available Taking the maximum vehicle driving distance, the distances from gas stations, the route length, and the number of refueling gas stations as the decision conditions, recommendation rules and an early refueling service warning mechanism for gas stations along a self-driving travel route were constructed by using the algorithm presented in this research, based on the spatial clustering characteristics of gas stations and the urgency of refueling. Meanwhile, by combining ArcEngine and Matlab capabilities, a scenario simulation system of refueling for self-driving travel was developed by using c#.net in order to validate and test the accuracy and applicability of the algorithm. A total of nine testing schemes with four simulation scenarios were designed and executed using this algorithm, and all of the simulation results were consistent with expectations. The refueling recommendation algorithm proposed in this study can automatically adapt to changes in the route length of self-driving travel, the maximum driving distance of the vehicle, and the distance from gas stations, which could provide variable refueling recommendation strategies according to differing gas station layouts along the route. Therefore, the results of this study could provide a scientific reference for the reasonable planning and timely supply of vehicle refueling during self-driving travel.

Development and Validation of Reentry Simulation Using MATLAB

National Research Council Canada - National Science Library

Jameson, Jr, Robert E

2006-01-01

This research effort develops a program using MATLAB to solve the equations of motion for atmospheric reentry and analyzes the validity of the program for use as a tool to expeditiously predict reentry profiles...

Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework

International Nuclear Information System (INIS)

Machnes, S.; Sander, U.; Glaser, S. J.; Schulte-Herbrueggen, T.; Fouquieres, P. de; Gruslys, A.; Schirmer, S.

2011-01-01

For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.

A Compilation of MATLAB Scripts and Functions for MACGMC Analyses

Science.gov (United States)

Murthy, Pappu L. N.; Bednarcyk, Brett A.; Mital, Subodh K.

2017-01-01

The primary aim of the current effort is to provide scripts that automate many of the repetitive pre- and post-processing tasks associated with composite materials analyses using the Micromechanics Analysis Code with the Generalized Method of Cells. This document consists of a compilation of hundreds of scripts that were developed in MATLAB (The Mathworks, Inc., Natick, MA) programming language and consolidated into 16 MATLAB functions. (MACGMC). MACGMC is a composite material and laminate analysis software code developed at NASA Glenn Research Center. The software package has been built around the generalized method of cells (GMC) family of micromechanics theories. The computer code is developed with a user-friendly framework, along with a library of local inelastic, damage, and failure models. Further, application of simulated thermo-mechanical loading, generation of output results, and selection of architectures to represent the composite material have been automated to increase the user friendliness, as well as to make it more robust in terms of input preparation and code execution. Finally, classical lamination theory has been implemented within the software, wherein GMC is used to model the composite material response of each ply. Thus, the full range of GMC composite material capabilities is available for analysis of arbitrary laminate configurations as well. The pre-processing tasks include generation of a multitude of different repeating unit cells (RUCs) for CMCs and PMCs, visualization of RUCs from MACGMC input and output files and generation of the RUC section of a MACGMC input file. The post-processing tasks include visualization of the predicted composite response, such as local stress and strain contours, damage initiation and progression, stress-strain behavior, and fatigue response. In addition to the above, several miscellaneous scripts have been developed that can be used to perform repeated Monte-Carlo simulations to enable probabilistic

Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications

Science.gov (United States)

Qian, Xuewen; Deng, Honggui; He, Hailang

2017-10-01

Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.

Structure-Based Algorithms for Microvessel Classification

KAUST Repository

Smith, Amy F.

2015-02-01

© 2014 The Authors. Microcirculation published by John Wiley & Sons Ltd. Objective: Recent developments in high-resolution imaging techniques have enabled digital reconstruction of three-dimensional sections of microvascular networks down to the capillary scale. To better interpret these large data sets, our goal is to distinguish branching trees of arterioles and venules from capillaries. Methods: Two novel algorithms are presented for classifying vessels in microvascular anatomical data sets without requiring flow information. The algorithms are compared with a classification based on observed flow directions (considered the gold standard), and with an existing resistance-based method that relies only on structural data. Results: The first algorithm, developed for networks with one arteriolar and one venular tree, performs well in identifying arterioles and venules and is robust to parameter changes, but incorrectly labels a significant number of capillaries as arterioles or venules. The second algorithm, developed for networks with multiple inlets and outlets, correctly identifies more arterioles and venules, but is more sensitive to parameter changes. Conclusions: The algorithms presented here can be used to classify microvessels in large microvascular data sets lacking flow information. This provides a basis for analyzing the distinct geometrical properties and modelling the functional behavior of arterioles, capillaries, and venules.

Changing patient population in Dhaka Hospital and Matlab Hospital of icddr,b.

Science.gov (United States)

Das, S K; Rahman, A; Chisti, M J; Ahmed, S; Malek, M A; Salam, M A; Bardhan, P K; Faruque, A S G

2014-02-01

The Diarrhoeal Disease Surveillance System of icddr,b noted increasing number of patients ≥60 years at urban Dhaka and rural Matlab from 2001 to 2012. Shigella and Vibrio cholerae were more frequently isolated from elderly people than children under 5 years and adults aged 5-59 in both areas. The resistance observed to various drugs of Shigella in Dhaka and Matlab was trimethoprim-sulphamethoxazole (72-63%), ampicillin (43-55%), nalidixic acid (58-61%), mecillinam (12-9%), azithromycin (13-0%), ciprofloxacin (11-13%) and ceftriaxone (11-0%). Vibrio cholerae isolated in Dhaka and Matlab was resistant to trimethoprim-sulphamethoxazole (98-94%), furazolidone (100%), erythromycin (71-53%), tetracycline (46-44%), ciprofloxacin (3-10%) and azithromycin (3-0%). © 2013 John Wiley & Sons Ltd.

Algorithm for detection of the broken phase conductor in the radial networks

Directory of Open Access Journals (Sweden)

Ostojić Mladen M.

2016-01-01

Full Text Available The paper presents an algorithm for a directional relay to be used for a detection of the broken phase conductor in the radial networks. The algorithm would use synchronized voltages, measured at the beginning and at the end of the line, as input signals. During the process, the measured voltages would be phase-compared. On the basis of the normalized energy, the direction of the phase conductor, with a broken point, would be detected. Software tool Matlab/Simulink package has developed a radial network model which simulates the broken phase conductor. The simulations generated required input signals by which the algorithm was tested. Development of the algorithm along with the formation of the simulation model and the test results of the proposed algorithm are presented in this paper.

Change Detection Algorithms for Surveillance in Visual IoT: A Comparative Study

Science.gov (United States)

Akram, Beenish Ayesha; Zafar, Amna; Akbar, Ali Hammad; Wajid, Bilal; Chaudhry, Shafique Ahmad

2018-01-01

The VIoT (Visual Internet of Things) connects virtual information world with real world objects using sensors and pervasive computing. For video surveillance in VIoT, ChD (Change Detection) is a critical component. ChD algorithms identify regions of change in multiple images of the same scene recorded at different time intervals for video surveillance. This paper presents performance comparison of histogram thresholding and classification ChD algorithms using quantitative measures for video surveillance in VIoT based on salient features of datasets. The thresholding algorithms Otsu, Kapur, Rosin and classification methods k-means, EM (Expectation Maximization) were simulated in MATLAB using diverse datasets. For performance evaluation, the quantitative measures used include OSR (Overall Success Rate), YC (Yule's Coefficient) and JC (Jaccard's Coefficient), execution time and memory consumption. Experimental results showed that Kapur's algorithm performed better for both indoor and outdoor environments with illumination changes, shadowing and medium to fast moving objects. However, it reflected degraded performance for small object size with minor changes. Otsu algorithm showed better results for indoor environments with slow to medium changes and nomadic object mobility. k-means showed good results in indoor environment with small object size producing slow change, no shadowing and scarce illumination changes.

Novel prediction- and subblock-based algorithm for fractal image compression

International Nuclear Information System (INIS)

Chung, K.-L.; Hsu, C.-H.

2006-01-01

Fractal encoding is the most consuming part in fractal image compression. In this paper, a novel two-phase prediction- and subblock-based fractal encoding algorithm is presented. Initially the original gray image is partitioned into a set of variable-size blocks according to the S-tree- and interpolation-based decomposition principle. In the first phase, each current block of variable-size range block tries to find the best matched domain block based on the proposed prediction-based search strategy which utilizes the relevant neighboring variable-size domain blocks. The first phase leads to a significant computation-saving effect. If the domain block found within the predicted search space is unacceptable, in the second phase, a subblock strategy is employed to partition the current variable-size range block into smaller blocks to improve the image quality. Experimental results show that our proposed prediction- and subblock-based fractal encoding algorithm outperforms the conventional full search algorithm and the recently published spatial-correlation-based algorithm by Truong et al. in terms of encoding time and image quality. In addition, the performance comparison among our proposed algorithm and the other two algorithms, the no search-based algorithm and the quadtree-based algorithm, are also investigated

Introducing Effects in an Image: A MATLAB Approach

OpenAIRE

Kumar , Vinay; Sood , Saurabh; Mishra , Shruti

2008-01-01

A detailed study of introducing morning, night, and some more effect in an image is discussed, the original image is clicked in the morning. Several examples have also been discussed. MATLAB is used for the processing.

A homotopy algorithm for digital optimal projection control GASD-HADOC

Science.gov (United States)

Collins, Emmanuel G., Jr.; Richter, Stephen; Davis, Lawrence D.

1993-01-01

The linear-quadratic-gaussian (LQG) compensator was developed to facilitate the design of control laws for multi-input, multi-output (MIMO) systems. The compensator is computed by solving two algebraic equations for which standard closed-loop solutions exist. Unfortunately, the minimal dimension of an LQG compensator is almost always equal to the dimension of the plant and can thus often violate practical implementation constraints on controller order. This deficiency is especially highlighted when considering control-design for high-order systems such as flexible space structures. This deficiency motivated the development of techniques that enable the design of optimal controllers whose dimension is less than that of the design plant. A homotopy approach based on the optimal projection equations that characterize the necessary conditions for optimal reduced-order control. Homotopy algorithms have global convergence properties and hence do not require that the initializing reduced-order controller be close to the optimal reduced-order controller to guarantee convergence. However, the homotopy algorithm previously developed for solving the optimal projection equations has sublinear convergence properties and the convergence slows at higher authority levels and may fail. A new homotopy algorithm for synthesizing optimal reduced-order controllers for discrete-time systems is described. Unlike the previous homotopy approach, the new algorithm is a gradient-based, parameter optimization formulation and was implemented in MATLAB. The results reported may offer the foundation for a reliable approach to optimal, reduced-order controller design.

MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming

Directory of Open Access Journals (Sweden)

Yuteng Xiao

2017-01-01

Full Text Available Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamforming algorithm is MVDR (Minimum Variance Distortionless Response. However, the performance of MVDR algorithm relies on the accurate covariance matrix. The MVDR algorithm declines dramatically with the inaccurate covariance matrix. To solve the problem, studying the beamforming array signal model and beamforming MVDR algorithm, we improve MVDR algorithm based on estimated diagonal loading for beamforming. MVDR optimization model based on diagonal loading compensation is established and the interval of the diagonal loading compensation value is deduced on the basis of the matrix theory. The optimal diagonal loading value in the interval is also determined through the experimental method. The experimental results show that the algorithm compared with existing algorithms is practical and effective.

Pulseq-Graphical Programming Interface: Open source visual environment for prototyping pulse sequences and integrated magnetic resonance imaging algorithm development.

Science.gov (United States)

Ravi, Keerthi Sravan; Potdar, Sneha; Poojar, Pavan; Reddy, Ashok Kumar; Kroboth, Stefan; Nielsen, Jon-Fredrik; Zaitsev, Maxim; Venkatesan, Ramesh; Geethanath, Sairam

2018-03-11

To provide a single open-source platform for comprehensive MR algorithm development inclusive of simulations, pulse sequence design and deployment, reconstruction, and image analysis. We integrated the "Pulseq" platform for vendor-independent pulse programming with Graphical Programming Interface (GPI), a scientific development environment based on Python. Our integrated platform, Pulseq-GPI, permits sequences to be defined visually and exported to the Pulseq file format for execution on an MR scanner. For comparison, Pulseq files using either MATLAB only ("MATLAB-Pulseq") or Python only ("Python-Pulseq") were generated. We demonstrated three fundamental sequences on a 1.5 T scanner. Execution times of the three variants of implementation were compared on two operating systems. In vitro phantom images indicate equivalence with the vendor supplied implementations and MATLAB-Pulseq. The examples demonstrated in this work illustrate the unifying capability of Pulseq-GPI. The execution times of all the three implementations were fast (a few seconds). The software is capable of user-interface based development and/or command line programming. The tool demonstrated here, Pulseq-GPI, integrates the open-source simulation, reconstruction and analysis capabilities of GPI Lab with the pulse sequence design and deployment features of Pulseq. Current and future work includes providing an ISMRMRD interface and incorporating Specific Absorption Ratio and Peripheral Nerve Stimulation computations. Copyright © 2018 Elsevier Inc. All rights reserved.

Scientific computing with MATLAB and Octave

CERN Document Server

Quarteroni, Alfio; Gervasio, Paola

2014-01-01

This textbook is an introduction to Scientific Computing, in which several numerical methods for the computer-based solution of certain classes of mathematical problems are illustrated. The authors show how to compute the zeros, the extrema, and the integrals of continuous functions, solve linear systems, approximate functions using polynomials and construct accurate approximations for the solution of ordinary and partial differential equations. To make the format concrete and appealing, the programming environments Matlab and Octave are adopted as faithful companions. The book contains the solutions to several problems posed in exercises and examples, often originating from important applications. At the end of each chapter, a specific section is devoted to subjects which were not addressed in the book and contains bibliographical references for a more comprehensive treatment of the material. From the review: ".... This carefully written textbook, the third English edition, contains substantial new developme...

MATLAB/SIMULINK model of CANDU reactor for control studies

International Nuclear Information System (INIS)

Javidnia, H.; Jiang, J.

2006-01-01

In this paper a MATLAB/SIMULINK model is developed for a CANDU type reactor. The data for the reactor are taken from an Indian PHWR, which is very similar to CANDU in its design. Among the different feedback mechanisms in the core of the reactor, only xenon has been considered which plays an important role in spatial oscillations. The model is verified under closed loop scenarios with simple PI controller. The results of the simulation show that this model can be used for controller design and simulation of the reactor systems. Adding models of the other components of a CANDU reactor would ultimately result in a complete model of CANDU plant in MATLAB/SIMULINK. (author)

Optimisation of groundwater level monitoring networks using geostatistical modelling based on the Spartan family variogram and a genetic algorithm method

Science.gov (United States)

Parasyris, Antonios E.; Spanoudaki, Katerina; Kampanis, Nikolaos A.

2016-04-01

Groundwater level monitoring networks provide essential information for water resources management, especially in areas with significant groundwater exploitation for agricultural and domestic use. Given the high maintenance costs of these networks, development of tools, which can be used by regulators for efficient network design is essential. In this work, a monitoring network optimisation tool is presented. The network optimisation tool couples geostatistical modelling based on the Spartan family variogram with a genetic algorithm method and is applied to Mires basin in Crete, Greece, an area of high socioeconomic and agricultural interest, which suffers from groundwater overexploitation leading to a dramatic decrease of groundwater levels. The purpose of the optimisation tool is to determine which wells to exclude from the monitoring network because they add little or no beneficial information to groundwater level mapping of the area. Unlike previous relevant investigations, the network optimisation tool presented here uses Ordinary Kriging with the recently-established non-differentiable Spartan variogram for groundwater level mapping, which, based on a previous geostatistical study in the area leads to optimal groundwater level mapping. Seventy boreholes operate in the area for groundwater abstraction and water level monitoring. The Spartan variogram gives overall the most accurate groundwater level estimates followed closely by the power-law model. The geostatistical model is coupled to an integer genetic algorithm method programmed in MATLAB 2015a. The algorithm is used to find the set of wells whose removal leads to the minimum error between the original water level mapping using all the available wells in the network and the groundwater level mapping using the reduced well network (error is defined as the 2-norm of the difference between the original mapping matrix with 70 wells and the mapping matrix of the reduced well network). The solution to the

DISTRIBUTION NETWORK RECONFIGURATION FOR POWER LOSS MINIMIZATION AND VOLTAGE PROFILE ENHANCEMENT USING ANT LION ALGORITHM

Directory of Open Access Journals (Sweden)

Maryam Shokouhi

2017-06-01

Full Text Available Distribution networks are designed as a ring and operated as a radial form. Therefore, the reconfiguration is a simple and cost-effective way to use existing facilities without the need for any new equipment in distribution networks to achieve various objectives such as: power loss reduction, feeder overload reduction, load balancing, voltage profile improvement, reducing the number of switching considering constraints that ultimately result in the power loss reduction. In this paper, a new method based on the Ant Lion algorithm (a modern meta-heuristic algorithm is provided for the reconfiguration of distribution networks. Considering the extension of the distribution networks and complexity of their communications networks, and the various parameters, using smart techniques is inevitable. The proposed approach is tested on the IEEE 33 & 69-bus radial standard distribution networks. The Evaluation of results in MATLAB software shows the effectiveness of the Ant Lion algorithm in the distribution network reconfiguration.

Matlab/Simulink-based simulation for digital-control system of marine three-shaft gas-turbine

International Nuclear Information System (INIS)

Yu Youhong; Chen Lingen; Sun Fengrui; Wu Chih

2005-01-01

A gas-turbine plant model is required in order to design and develop its control system. In this paper, a simulation model of a marine three-shaft gas-turbine's digital-control system is presented. Acceleration processes are simulated via a Matlab/Simulink program. The effects of some of the main variables on the system's performance are analyzed and the optimum values of parameters obtained. A simulation experiment upon a real gas-turbine plant is performed using the digital-control model. The results show that the simulation model is reliable

[A new peak detection algorithm of Raman spectra].

Science.gov (United States)

Jiang, Cheng-Zhi; Sun, Qiang; Liu, Ying; Liang, Jing-Qiu; An, Yan; Liu, Bing

2014-01-01

The authors proposed a new Raman peak recognition method named bi-scale correlation algorithm. The algorithm uses the combination of the correlation coefficient and the local signal-to-noise ratio under two scales to achieve Raman peak identification. We compared the performance of the proposed algorithm with that of the traditional continuous wavelet transform method through MATLAB, and then tested the algorithm with real Raman spectra. The results show that the average time for identifying a Raman spectrum is 0.51 s with the algorithm, while it is 0.71 s with the continuous wavelet transform. When the signal-to-noise ratio of Raman peak is greater than or equal to 6 (modern Raman spectrometers feature an excellent signal-to-noise ratio), the recognition accuracy with the algorithm is higher than 99%, while it is less than 84% with the continuous wavelet transform method. The mean and the standard deviations of the peak position identification error of the algorithm are both less than that of the continuous wavelet transform method. Simulation analysis and experimental verification prove that the new algorithm possesses the following advantages: no needs of human intervention, no needs of de-noising and background removal operation, higher recognition speed and higher recognition accuracy. The proposed algorithm is operable in Raman peak identification.

Analysis of Parametric Optimization of Field-Oriented Control of 3-Phase Induction Motor with Using Evolutionary Algorithm

Directory of Open Access Journals (Sweden)

Wiktor HUDY

2013-12-01

Full Text Available In this paper, the impact of regulators set and their types for the characteristic of rotational speed of induction motor was researched.. The evolutionary algorithm was used as optimization tool. Results were verified with using MATLAB/Simulink.

SIPPI: A Matlab toolbox for sampling the solution to inverse problems with complex prior information

DEFF Research Database (Denmark)

Hansen, Thomas Mejer; Cordua, Knud Skou; Looms, Majken Caroline

2013-01-01

We present an application of the SIPPI Matlab toolbox, to obtain a sample from the a posteriori probability density function for the classical tomographic inversion problem. We consider a number of different forward models, linear and non-linear, such as ray based forward models that rely...

A Collection of Nonlinear Aircraft Simulations in MATLAB

Science.gov (United States)

Garza, Frederico R.; Morelli, Eugene A.

2003-01-01

Nonlinear six degree-of-freedom simulations for a variety of aircraft were created using MATLAB. Data for aircraft geometry, aerodynamic characteristics, mass / inertia properties, and engine characteristics were obtained from open literature publications documenting wind tunnel experiments and flight tests. Each nonlinear simulation was implemented within a common framework in MATLAB, and includes an interface with another commercially-available program to read pilot inputs and produce a three-dimensional (3-D) display of the simulated airplane motion. Aircraft simulations include the General Dynamics F-16 Fighting Falcon, Convair F-106B Delta Dart, Grumman F-14 Tomcat, McDonnell Douglas F-4 Phantom, NASA Langley Free-Flying Aircraft for Sub-scale Experimental Research (FASER), NASA HL-20 Lifting Body, NASA / DARPA X-31 Enhanced Fighter Maneuverability Demonstrator, and the Vought A-7 Corsair II. All nonlinear simulations and 3-D displays run in real time in response to pilot inputs, using contemporary desktop personal computer hardware. The simulations can also be run in batch mode. Each nonlinear simulation includes the full nonlinear dynamics of the bare airframe, with a scaled direct connection from pilot inputs to control surface deflections to provide adequate pilot control. Since all the nonlinear simulations are implemented entirely in MATLAB, user-defined control laws can be added in a straightforward fashion, and the simulations are portable across various computing platforms. Routines for trim, linearization, and numerical integration are included. The general nonlinear simulation framework and the specifics for each particular aircraft are documented.

Algorithm Research of Individualized Travelling Route Recommendation Based on Similarity

Directory of Open Access Journals (Sweden)

Xue Shan

2015-01-01

Full Text Available Although commercial recommendation system has made certain achievement in travelling route development, the recommendation system is facing a series of challenges because of people’s increasing interest in travelling. It is obvious that the core content of the recommendation system is recommendation algorithm. The advantages of recommendation algorithm can bring great effect to the recommendation system. Based on this, this paper applies traditional collaborative filtering algorithm for analysis. Besides, illustrating the deficiencies of the algorithm, such as the rating unicity and rating matrix sparsity, this paper proposes an improved algorithm combing the multi-similarity algorithm based on user and the element similarity algorithm based on user, so as to compensate for the deficiencies that traditional algorithm has within a controllable range. Experimental results have shown that the improved algorithm has obvious advantages in comparison with the traditional one. The improved algorithm has obvious effect on remedying the rating matrix sparsity and rating unicity.

Research of PV Power Generation MPPT based on GABP Neural Network

Science.gov (United States)

Su, Yu; Lin, Xianfu

2018-05-01

Photovoltaic power generation has become the main research direction of new energy power generation. But high investment and low efficiency of photovoltaic industry arouse concern in some extent. So maximum power point tracking of photovoltaic power generation has been a popular study point. Due to slow response, oscillation at maximum power point and low precision, the algorithm based on genetic algorithm combined with BP neural network are designed detailedly in this paper. And the modeling and simulation are completed by use of MATLAB/SIMULINK. The results show that the algorithm is effective and the maximum power point can be tracked accurately and quickly.

Duality based optical flow algorithms with applications

DEFF Research Database (Denmark)

Rakêt, Lars Lau

We consider the popular TV-L1 optical flow formulation, and the so-called duality based algorithm for minimizing the TV-L1 energy. The original formulation is extended to allow for vector valued images, and minimization results are given. In addition we consider different definitions of total...... variation regularization, and related formulations of the optical flow problem that may be used with a duality based algorithm. We present a highly optimized algorithmic setup to estimate optical flows, and give five novel applications. The first application is registration of medical images, where X......-ray images of different hands, taken using different imaging devices are registered using a TV-L1 optical flow algorithm. We propose to regularize the input images, using sparsity enhancing regularization of the image gradient to improve registration results. The second application is registration of 2D...

LMI-Based H¥ Anti-Rollover Control Algorithm of Vehicle Active Suspension

Directory of Open Access Journals (Sweden)

LIAO Cong

2014-10-01

Full Text Available In order to improve the anti-rollover ability for vehicles, a 4 DOF vehicle rollover dynamics model is established, base on which we have designed an active suspension anti-rollover controller and proposed the H¥ control strategy. Simulations were carried out using Matlab/Simulink, and results show that the proposed control scheme can not only reduce the roll angle and roll angular velocity, but also improve the rollover stability of the vehicle and reduce the probability of vehicle rollover accidents.

The use of MATLAB-SIMULINK for evaluation of thermal building behavior; O uso do MATLAB-SIMULINK para avaliacao do comportamento termico de ambientes

Energy Technology Data Exchange (ETDEWEB)

Mendes, Nathan; Oliveira, Gustavo H.C.; Araujo, Humberto X. de [Pontificia Universidade Catolica do Parana, Curitiba, PR (Brazil). Lab. de Sistemas Termicos]|[Pontificia Universidade Catolica do Parana, Curitiba, PR (Brazil). Lab. de Automacao e Sistemas]. E-mail: nmendes@ccet.pucpr.br; oliv@ ccet.pucpr.br; araujo@ ccet.pucpr.br

2000-07-01

We describe a mathematical model applied to both building thermal analysis and control systems design. We use a lumped approach to model the room air temperature and a multi-layer model for the building envelope. The capacitance model allows to study the transient analysis of room air temperature when it is submitted to sinusoidal variation of external air temperature, representing a case study for the city of Curitiba-PR, Brazil. To evaluate the building performance with thermal parameters, we use MATLAB/SIMULINK. In the results section, we show the influences of thermal capacitance on the building air temperature and energy consumption and the advantages of using MATLAB/SIMULINK in building thermal and energy analysis as well. (author)

Efficient topology optimization in MATLAB using 88 lines of code

DEFF Research Database (Denmark)

Andreassen, Erik; Clausen, Anders; Schevenels, Mattias

2011-01-01

The paper presents an efficient 88 line MATLAB code for topology optimization. It has been developed using the 99 line code presented by Sigmund (Struct Multidisc Optim 21(2):120–127, 2001) as a starting point. The original code has been extended by a density filter, and a considerable improvemen...... of the basic code to include recent PDE-based and black-and-white projection filtering methods. The complete 88 line code is included as an appendix and can be downloaded from the web site www.topopt.dtu.dk....

Optimization of the Compensation of a Meshed MV Network by a Modified Genetic Algorithm

DEFF Research Database (Denmark)

Nielsen, Hans; Paar, M.; Toman, P.

2007-01-01

The article discusses the utilization of a modified genetic algorithm (GA) for the optimization of the shunt compensation in meshed and radial MV distribution networks. The algorithm looks for minimum costs of the network power losses and minimum capital and operating costs of applied capacitors......, all of this under limitations specified by a multicriteria penalization function. The parallel evolution branches in the GA are used for the purpose of the optimization accelaration. The application of this GA has been implemented in Matlab. The evaluation part of the GA implementation is based...... on the steady-state analysis using a linear one-line diagram model of a power network. The results of steady-state solutions are compared with the results from the DIgSILENT PowerFactory program. Its practical applicability is demonstrated on examples of 22 kV and meshed overhead distribution networks....

Evidence-based algorithm for heparin dosing before cardiopulmonary bypass. Part 1: Development of the algorithm.

Science.gov (United States)