The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are presently scattered in different fields. There remains a need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. This book attempts to satisfy the above requirement. The algorithms are made clear using MATLAB programs.
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Editorial Reviews
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From the reviews: “The presented book is devoted to the realization of the Digital Signal Processing (DSP) algorithms, using Matlab. … The book is written in such a way that it is suitable for non-mathematical readers and is very much suitable for the beginners who are doing research in Digital Signal Processing.” (Tzvetan Semerdjiev, Zentralblatt MATH, Vol. 1189, 2010)
From the Back Cover
The Algorithms such as SVD, Eigen decomposition, Gaussian Mixture Model, HMM etc. are scattered in different fields. There is the need to collect all such algorithms for quick reference. Also there is the need to view such algorithms in application point of view. Algorithm Collections for Digital Signal Processing Applications using MATLAB attempts to satisfy the above requirement. Also the algorithms are made clear using MATLAB programs.
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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numerical linear algebra, weight matrix, fuzzy base rule, figure imshow, updating pheromone matrix, particular subblock, figure subplot, eigen basis, eigen matrix, variance normalization, rank for image, crisp value, covariance matrix computed, collected vectors, fuzzy membership value, photo realistic images, ear image Key Phrases - Capitalized Phrases (CAPs): (learn more)
Selected Applications, Artificial Intelligence, Neural Network, Crisp Value Figure, Algorithm Step, Algorithm Collections, Illustration of Simulated Annealing, Biological Genetics, Example Let, Approach Step, Genetic Algorithm, Program Illustration, Number of Eigen, Corrupted Signal Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
numerical linear algebra, weight matrix, fuzzy base rule, figure imshow, updating pheromone matrix, particular subblock, figure subplot, eigen basis, eigen matrix, variance normalization, rank for image, crisp value, covariance matrix computed, collected vectors, fuzzy membership value, photo realistic images, ear image Key Phrases - Capitalized Phrases (CAPs): (learn more)
Selected Applications, Artificial Intelligence, Neural Network, Crisp Value Figure, Algorithm Step, Algorithm Collections, Illustration of Simulated Annealing, Biological Genetics, Example Let, Approach Step, Genetic Algorithm, Program Illustration, Number of Eigen, Corrupted Signal Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Surprise Me!
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