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Audio Source Separation

-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non;

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Factorization of Matrix and Operator Functions

This book delineates the various types of factorization problems for matrix and operator functions. The problems originate from, or are;

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Foundations of Data Science

topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed;

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Non negative Matrix Factorization Techniques

This book collects new results, concepts and further developments of NMF. The open problems discusse;...

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Non-negative Matrix Factorization Techniques

This book collects new results, concepts and further developments of NMF. The open problems discusse;...

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Regularization, Optimization, Kernels, and Support Vector Machines

-negative matrix factorization Examines low-rank matrix and tensor-based models Presents advanced kernel methods for batch and online machine;

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Regularization, Optimization, Kernels, and Support Vector Machines

portfolio selection Addresses non-negative matrix factorization Examines low-rank matrix and tensor-based models Presents;

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An Operator Perspective on Signals and Systems

In this monograph, we combine operator techniques with state space methods to solve factorization, spectral estimation, and interpolation;

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Non-Destructive Evaluation (NDE) of Polymer Matrix Composites

control and testing of products to ensure and monitor performance over time. Non-destructive evaluation (NDE) of polymer matrix composites;

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Matrix Theory

algebra. In answer to this recommendation, Matrix Theory: From Generalized Inverses to Jordan Form provides the material for a second semester;

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Matrix Theory

algebra. In answer to this recommendation, Matrix Theory: From Generalized Inverses to Jordan Form provides the material for a second semester;

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Fireworks Algorithm

combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix;

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Non-Negative Matrix And Tensor Factorizations

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF's;

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Computation of Generalized Matrix Inverses and Applications

This volume offers a gradual exposition to matrix theory as a subject of linear algebra. It presents both the theoretical results;

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Computation of Generalized Matrix Inverses and Applications

This volume offers a gradual exposition to matrix theory as a subject of linear algebra. It presents both the theoretical results;

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Applied Recommender Systems with Python

collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering;

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Applied Recommender Systems with Python

collaborative filtering using matrix factorization and hybrid recommender systems that incorporate both content-based and collaborative filtering;

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Factorization of Boundary Value Problems Using the Invariant Embedding Method

successively. This method appears similar to the Gauss block factorization of the matrix, obtained in finite dimension after discretization of the;

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Factorization Methods for Discrete Sequential Estimation

This estimation reference text thoroughly describes matrix factorization methods successfully employed by numerical analysts, familiarizing;

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A DIFFERENT FUTURE - An Introduction to an Esoteric Form of Raja Yoga

techniques for the body, mind and feeling and adds healing techniques to developmental ones. Apart from a new synthesis of traditional ideas original;

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Introduction to Matrix Theory

various factorizations such as rank factorization, OR-factorization, Schurtriangularization, Diagonalization of normal matrices, Jordan;

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Blind Source Separation

). The last part of the book considers the very recent algorithms in BSS e.g. Sparse Component Analysis (SCA) and Non-negative Matrix;

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Signal and Image Processing for Remote Sensing

representation, as well as new component analysis methods such as non-negative matrix and tensor factorization. The book also presents new experimental;

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Handbook of Robust Low-Rank and Sparse Matrix Decomposition

analysis (PCA) via decomposition into low-rank and sparse matrices. The second part addresses robust matrix factorization/completion problems while;

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Advances in Medicine & Biology

activation and joint movement with muscle synergy extraction via non-negative matrix factorization. Chapter Four examines lupus anticoagulant and;

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Optimal and Robust Control

There are many books on advanced control for specialists, but not many present these topics for non-specialists. Assuming only a basic;

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Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett

of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including;

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