This book was written to provide resource materials for teachers to use in their introductory or intermediate statistics class. The chapter content is ordered along the lines of many popular statistics books so it should be easy to supplement the content and exercises with class lecture materials.
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their...
The complete updated edition of this best-selling reference provides an unsurpassed account of process control--from the very basics of theory to advanced control applications. This edition of this guide fully explains control technology principles applied to industrial fluid processes, including time-domain and relative-gain analysis. Control...
Many books already exist on the topics of digital control and estimation. The prospective reader of this book might well then ask. "why another book in this area?"
One problem with the existing literature is that it emphasizes the differences between discrete and continuous theory. This dichotomy is largely...
A comprehensive, must-have handbook of matrix methods with a unique emphasis on statistical applications
This timely book, A Matrix Handbook for Statisticians, provides a comprehensive, encyclopedic treatment of matrices as they relate to both statistical concepts and methodologies. Written by an experienced authority on matrices and...
Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today’s powerful computing capabilities, they can be used in a wide range of application areas, including...
Embedded computer systems are electronic systems that include a microcomputer to perform
specific dedicated tasks. The computer is hidden inside these products. Embedded
systems are ubiquitous. Every week millions of tiny computer chips come pouring out
of factories like Freescale, Microchip, Philips, Texas Instruments, Silicon Labs,...
At the heart of every medical imaging technology is a sophisticated mathematical model of the measurement process and an algorithm to reconstruct an image from the measured data. This book provides a firm foundation in the mathematical tools used to model the measurements and derive the reconstruction algorithms used in most imaging modalities in...
Everyone encounters statistics on a daily basis. They are used in proposals, reports, requests, and advertisements, among others, to support assertions, opinions, and theories. Unless you’re a trained statistician, it can be bewildering. What are the numbers really saying or not saying? Better Business Decisions from Data:...
Although DSP has long been considered an EE topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware...
Amazon.com’s Top-Selling DSP Book for Seven Straight Years—Now Fully Updated!
Understanding Digital Signal Processing, Third Edition, is quite simply the best resource for engineers and other technical professionals who want to master and apply today’s latest DSP...
This new book by Ken Steigliz offers an informal and easy-to-understand introduction to digital signal processing, emphasizing digital audio and applications to computer music. A DSP Primer covers important topics such as phasors and tuning forks; the wave equation; sampling and quantizing; feedforward and feedback filters; comb and string...
