Introduction to Digital Filters: with Audio Applications
by Julius O. Smith III
Publisher: W3K Publishing 2007
Number of pages: 478
A digital filter can be pictured as a “black box” that accepts a sequence of numbers and emits a new sequence of numbers. In digital audio signal processing applications, such number sequences usually represent sounds. For example, digital filters are used to implement graphic equalizers and other digital audio effects. This book is a gentle introduction to digital filters, including mathematical theory, illustrative examples, some audio applications, and useful software starting points. The theory treatment begins at the high-school level, and covers fundamental concepts in linear systems theory and digital filter analysis. Various “small” digital filters are analyzed as examples, particularly those commonly used in audio applications. Matlab programming examples are emphasized for illustrating the use and development of digital filters in practice.
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by Paolo Prandoni, Martin Vetterli - EFPL Press
The book is less focused on the mathematics and more on the concepts, allowing students to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics and helping students solve real-world problems.
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.
by Vedran Kordic - InTech
The Kalman filter has been successfully employed in diverse knowledge areas over the last 50 years. The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and science.
by Raghu Raj Bahadur, at al. - IMS
In this volume the author covered what should be standard topics in a course of parametric estimation: Bayes estimates, unbiased estimation, Fisher information, Cramer-Rao bounds, and the theory of maximum likelihood estimation.