by Javier Prieto Tejedor (ed.)
Publisher: InTech 2017
Number of pages: 376
This book takes a look at both theoretical foundations of Bayesian inference and practical implementations in different fields. It is intended as an introductory guide for the application of Bayesian inference in the fields of life sciences, engineering, and economics, as well as a source document of fundamentals for intermediate Bayesian readers.
Home page url
Download or read it online for free here:
(multiple PDF files)
by Michael Wakin - Connexions
This book reviews fundamental concepts underlying the use of concise models for signal processing. Topics are presented from a geometric perspective and include low-dimensional linear, sparse, and manifold-based signal models, approximation, etc.
- Agilent Technologies
This text is a primer for those who are unfamiliar with the advantages of analysis in the frequency and modal domains and Dynamic Signal Analyzers. The authors avoid the use of rigorous mathematics and instead depend on heuristic arguments.
by Salih Mohammed Salih - InTech
This book focuses on the Fourier transform applications in signal processing techniques. Topics covered: DFT, FFT, OFDM, estimation techniques and the image processing techniques. Written for electrical engineers, communication engineers, etc.
by Walt Kester - Newnes
The book explains signal processing hardware. It covers sampled data systems, A-to-D and D-to-A converters for DSP applications, fast Fourier transforms, digital filters, DSP hardware, interfacing to DSP chips, hardware design techniques.