Digital Signal Processing Using MATLAB and WaveletsAlthough 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 circles. Designed for upper division engineering and computer science students as well as practicing engineers, Digital Signal Processing Using Matlab and Wavelets emphasizes the practical applications of signal processing. Over 100 Matlab projects 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. filters, sinusoids, sampling, the Fourier transform, the Z transform and other key topics. An entire chapter is dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects, and Microsoft[registered] PowerPoint slides. |
Contents
Summations | 27 |
Conditional Statements if | 35 |
Filters | 85 |
Sinusoids | 133 |
Sinusoids | 145 |
Sampling | 159 |
The Fourier Transform | 187 |
8 | 212 |
36 | 314 |
Applications | 339 |
A Constants and Variables Used in This Book | 399 |
Fourier Transform FT | 405 |
Convolution | 407 |
Wavelet Transform | 409 |
DSP Project Ideas | 411 |
About the CDROM | 415 |
The Number | 225 |
1 | 254 |
6 | 261 |
30 | 275 |
35 | 288 |
E Answers to Selected Review Questions | 417 |
F Glossary | 439 |
| 445 | |
| 449 | |
Other editions - View all
Digital Signal Processing Using MATLAB & Wavelets added for testing purpose Michael Weeks Limited preview - 2010 |
Common terms and phrases
aax[n adx[n aliasing amplitude analog signal approximation array ax[n bdx[n binary bx[n calculate Cartesian command complex number convert convolution cosine function cx[n Daubechies digital signal Discrete Fourier Transform discrete wavelet transform disp(sprintf down-sampler dx[n equation Euler's formula example signal filter bank filter coefficients Finite Impulse Response FIR filter frequency component frequency magnitude response frequency response frequency-domain graph Haar transform highpass filter IHPF ILPF impulse function impulse response input signal input x[n integer inverse look lowpass filter MATLAB matrix means multiply negative octave original signal output y[n phase angles Phasor plot radians reconstruction replace represent result Rotating Phasor samples/second sampling frequency shows simple sinusoids spectrum subplot sum of sinusoids time-domain transfer function up-sampling values variable vector wavelet transform wd[n x-axis Xmag z-transform zd[n zero