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This book describes several modules of the Code Excited Linear Prediction (CELP) algorithm. The authors use the Federal Standard-1016 CELP;
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points of the Gaussian elimination algorithm. Discusses vector spaces and linear transformations using matrix computations. Takes advantage;
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the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as;
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Matrix Algorithms in MATLAB focuses on the MATLAB code implementations of matrix algorithms. The MATLAB codes presented in the book;
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algorithm in the MATLAB programming language is provided, as well as MATLAB code for several example applications discussed in the manuscript.;
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development efforts. The application of machine learning algorithm i.e. artificial neural networks application in software reliability prediction;
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Learn to use MATLAB as a useful computing tool for exploring traditional Digital Signal Processing (DSP) topics and solving problems to;
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methods for linear programming. In addition to presenting the theoretical and algorithmic background necessary for dealing with specific interior;
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or for use as a textbook in computational courses, Applied Numerical Linear Algebra Using MATLAB, provides the reader with numerous;
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design the widely-used LAPACK and ScaLAPACK linear algebra libraries, draws on this experience to present state-of-the-art techniques for these;
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This textbook provides a self-contained introduction to linear programming using MATLAB(R) software to elucidate the development;
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foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for;
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Embedding-based prediction method is investigated for compression of Light Field images based on the HEVC technology. A new linear prediction method;
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linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python;
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linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python;
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Choose the Correct Solution Method for Your Optimization Problem Optimization: Algorithms and Applications presents a variety;
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computations and the accompanying theory alongside the author's useful insights. The book presents the most important algorithms of numerical linear;
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on the author's extensive experience in GNSS receiver design. The MATLAB script developed for this book demonstrates most of the key theories;
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on the author's extensive experience in GNSS receiver design. The MATLAB script developed for this book demonstrates most of the key theories;
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essential for students to get training in numerical methods and computer programming. Here, the authors use both Matlab and SciLab software as well;
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essential for students to get training in numerical methods and computer programming. Here, the authors use both Matlab and SciLab software as well;
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For undergraduate and graduate courses in MATLAB or as a reference in courses where MATLAB is used. This text covers all essential aspects;
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Classfication, 2nd ed, (DH&S). The code contains all algorithms described in Duda as well as supporting algorithms for data generation and visualization;
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Offering radar-related software for the analysis and design of radar waveform and signal processing, Radar Signal Analysis and Processing;
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demonstrates the coupling between MATLAB and SOLIDWORKS (R) for design optimization. A wide variety of optimization problems are covered including;
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. This latest entry in the Georgia Tech Digital Signal Processing Laboratory Series a laboratory series for DSP which operates on PCs offers you;
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There is good reason to be excited about Linear Algebra. With the world becoming increasingly digital, Linear Algebra is gaining more and;
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