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Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge;
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Convex Optimization for Signal Processing and Communications: From Fundamentals to Applications provides fundamental background knowledge;
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experts, sets out the theoretical underpinnings of the subject and provides tutorials on a wide range of convex optimization applications;
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information needed to understand transceiver optimization in a single volume. It begins with a review of digital communication fundamentals, and then;
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presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various;
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presents practical algorithms based on both convex and nonconvex optimization approaches, as well as theoretical analyses that use various;
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design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key;
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This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization;
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Communication & Signal Processing involving topics such as: Communications Theory and Techniques, Communications Protocols and Standards;
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and services are continually arising, and future mobile communications offer new opportunities and exciting challenges for signal processing;
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This book comprises the peer-reviewed proceedings of the International Conference on Communications, Signal Processing and VLSI (IC2SV;
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observations of both signals and functions of signals-demonstrating how they can be solved more efficiently as convex optimization problems. The;
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, signal processing, and microelectronics engineering. Providing an interdisciplinary platform, it brings together leading academicians, scientists;
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, (non-convex) proximal techniques, and stochastic gradient descent Regularization, Optimization, Kernels, and Support Vector Machines;
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, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing;
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Signal Processing for Multistatic Radar Systems: Adaptive Waveform Selection, Optimal Geometries and Pseudolinear Tracking Algorithms;
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any online entitlements included with the product. Master the Signal Processing Concepts and Techniques Needed to Design and Operate;
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There have been significant developments in the design and application of algorithms for both one-dimensional signal processing and;
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, stochastic resonance, financial markets, optimization, pattern recognition, signal detection, speech processing, and sensor fusion. Intelligent;
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science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the sparsity;
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science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the;
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performance optimization techniques in VLSI signal processing. Based on Keshab Parhi's highly respected and popular graduate-level courses, this;
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over assorted wireless network scenarios, interweaving concepts from signal processing, optimization, information theory, communications and networking;
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in industry carrying out research into signal processing for communications, sonar, radar, navigation and biomedical applications, and to academic;
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This book brings together papers from the 2018 International Conference on Communications, Signal Processing, and Systems, which was held;
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, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the;
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This book brings together papers from the 2018 International Conference on Communications, Signal Processing, and Systems, which was held;
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