Signal Detection Epub

The task of signal detection is deciding whether signals of interest exist by using their observed data. Furthermore, signals are reconstructed or their key parameters are estimated from the observations in the task of signal recovery. Sparsity is a natural characteristic of most of signals in practice. The fact that multiple sparse signals share the common locations of dominant coefficients is called by joint sparsity. In the context of signal processing, joint sparsity model results in higher performance of signal detection and recovery. This book focuses on the task of detecting and reconstructing signals with joint sparsity. The main contents include key methods for detection of joint sparse signals and their corresponding theoretical performance analysis, and methods for joint sparse signal recovery and their application in the context of radar imaging.

This book is written for engineers who need to develop algorithms used for signal processing and/or implement algorithms using the C programming language or MATLAB. The book features a rich collection of recipes for applied signal processing such as FIR, IIR, FFT, correlation, complex FIR, adaptive filters and others. The book applies to those who want to implement in the shortest time to market working systems that are built from a collection of building blocks implemented in an FPGA firmware or C language software, running on an SBC or DSP. Structured as an instantly applicable guide, the author covers a wide collection of required solutions to common encountered problems with a software guide.

Methods of signal detection are becoming an ever more vital component of wireless services, as providers lean towards using multiple antennae to compensate for limitations in the available wireless spectrum. The co-authors of this book are two of the world’s leading authorities on so-called MIMO (multiple-input, multiple-output) systems, and here they share the key findings of their years of research. They detail a range of important techniques for signal detection when multiple transmitted and received signals are available.

This book is a broad-based introduction to an increasingly important topic. The overview is easy because each chapter is structured uniformly: theory, methods, realization alternatives, methodical and practical advantages and disadvantages, and examples from industrial technology and medicine as well as research and development practice.