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systems, encompassing standard mathematical tools as well as newer techniques such as wavelets and neural networks. C++ and Java implementations;
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applications to airborne, automotive and communications systems with the essential mathematical tools* Accompanying Matlab toolbox available on the web;
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theory and signal processing offer formal tools for the study of processes and measured quantities. This book shows that systems modeling;
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The mathematical tools used in signal analysis involve differential and difference equations, integral equations, matrix algebra and;
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An Introduction to Digital Signal Processing aims at undergraduate students who have basic knowledge in C programming, Circuit Theory;
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Scientific computing is a collection of tools, techniques and theories required to develop and solve mathematical models in science and;
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Scientific computing is a collection of tools, techniques and theories required to develop and solve mathematical models in science and;
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With solid theoretical foundations and numerous potential applications, Blind Signal Processing (BSP) is one of the hottest emerging areas;
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Written using clear and accessible language, this text provides detailed coverage of the core mathematical concepts underpinning signal;
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presenting key concepts and providing the mathematical foundations and advanced algorithms that are essential to the design of any signal processing;
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Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to;
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Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to;
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of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications;
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of convex optimization, while striking a balance between mathematical theory and applications in signal processing and communications;
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filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS;
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filter algorithms and implementations. Topics discussed include random signals and optimal processing, adaptive signal processing with the LMS;
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This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral;
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This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral;
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The mathematical tools used in signal analysis involve differential and difference equations, integral equations, matrix algebra and;
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A comprehensive, practical and up--to--date exposition on digital signal processing. Both mathematical and useful, this book uses a;
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Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the;
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signal processing algorithms is the main goal of this book. It starts with an overview of today's FPGA technology, devices and tools for;
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are working with XML in Java. It is a comprehensive tutorial and reference to the major APIs. This book shows developers how to: save XML;
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Digital Signal Processing: Concepts and Applications, second edition covers the basic principles and operation of DSP devices. Its aim;
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Digital Signal Processing: Concepts and Applications, second edition covers the basic principles and operation of DSP devices. Its aim;
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processing theory. Readers will learn this new approach to constructing the unified mathematical fundamentals of both information theory and signal;
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An ideal resource for students, industrial engineers, and researchers, Signal Processing with Free Software Practical Experiments presents;
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