รูปภาพสินค้า รหัส9780763784225
9780763784225
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ผู้เขียนMichael Weeks

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ราคาปก 3,440.00 บาท
ราคาสุทธิ 3,440.00 บาท
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รายละเอียดหนังสือ
รหัสสินค้า: 9780763784225
จำนวน: 516 หน้า
ขนาดรูปเล่ม: 192 x 239 x 32 มม.
น้ำหนัก: 1060 กรัม
เนื้อในพิมพ์: 2 สี 
ชนิดปก: ปกแข็ง 
ชนิดกระดาษ: กระดาษปอนด์ 
หน่วย: เล่ม 
สำนักพิมพ์: Jones and Bartlett Publishers, LLC. 
พิมพ์ครั้งล่าสุด:ครั้งที่ 2 เดือน -- ปี 2010
:: เนื้อหาโดยสังเขป
Although Digital Signal Processing (DSP) has long been considered an electrical engineering 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 circles. Designed for upper division engineering and computer science students as well as practicing engineers and scientists, Digital Signal Processing Using MATLAB & Wavelets, Second Edition emphasizes the practical applications of signal processing. Over 100 MATLAB examples and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound.

The book also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to MATLAB programming, it moves through filters, sinusoids, sampling, the Fourier transform, the z-transform and other key topics. Two chapters are dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects for each chapter, third-party simulations,and the figures contained in the book.
:: สารบัญ
1. Introduction
2. MATLAB
3. Filters
4. Sinusoids
5. Sampling
6. The Fourier Transform
7. The Transform
8. The Discrete Wavelet Transform
9. The Continuous Wavelet Transform
10. Applications