No BSD License
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AtoV(A,rN)
AtoV find reflection coefficients & system function
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R=randn(M,N)
RANDN Normally distributed random numbers and matrices from
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acf(x, m, w)
ACF compute autocorrelation function at m lags
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acf(x, m, w)
ACF compute autocorrelation function at m lags
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acimp(b, a, N)
ACIMP Calculate autocorrrelation sequence of an impulse
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asinc( x, L )
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atok(a)
ATOK converts AR polynomial to reflection coefficients
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autolpc(x, p)
AUTOLPC Autocorrelation Method for LPC
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ccf(x ,y, m, w);
CCF compute cross-correlation function at a few lags
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chirp( T, W, p )
CHIRP generate a sampled chirp signal
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chopfile(fname, L)
CHOPFILE break a long speech file into several smaller files
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comb(x, y, linetype)
COMB Plot discrete-time sequence data.
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comb(x, y, linetype)
COMB Plot discrete-time sequence data.
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comb(x, y, linetype)
COMB Plot discrete-time sequence data.
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convolm(x, num_zeros, pad)
CONVOLM Make convolution matrix, optionally padded with zeros
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dB( x, dBrange, dBmax )
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dtft(h, N)
DTFT calculate DTFT at N equally spaced frequencies
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factorit(n)
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flipDTFT(H, W)
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fmagplot( xa, dt )
FMAGPLOT Plot Fourier Transform (Mag) of "ANALOG" signal
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fplot( xa, dt )
FPLOT Plot Fourier Transform (Mag) of "ANALOG" signal
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fxquant( s, bit, rmode, lmode...
FXQUANT simulated fixed-point arithmetic
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gdel(x, n, Lfft)
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genint(N)
GENINT generate interference for TONE GENERATOR mystery signal
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genint(N)
GENINT generate interference for TONE GENERATOR mystery signal
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genint(N)
GENINT generate interference for TONE GENERATOR mystery signal
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gluedata(signal,n0,l)
GLUEDATA concatenate data segments of one long signal into one new data
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ktoa(k)
KTOA converts reflection coefficients to AR polynomial
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lchirp( T, W, p )
LCHIRP generate a sampled chirp signal with
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mod(x,N)
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mulaw(x, mu)
MULAW mu-law compression for signals with
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pcross( z, asize, azero )
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pcross( z, asize, azero )
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pcross( z, asize, azero )
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pkpicker( x, thresh, number, ...
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pronysyn( lam, c, nn )
PRONYSYN synthesize a sum of exponentials
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pseudinv(A, r)
PSEUDINV Pseudo-inverse of rank r.
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qplot(s, nbits, mu, ncases)
QPLOT for plotting dependence of signal-to-noise ratio
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radar( x, fs, T_0, g, T_out, ...
RADAR simulate radar returns from a single pulse
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speccomp(x, ncenter, win, nff...
SPECCOMP Plots spectra with hamming windows of different
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srexpand(x, L)
SREXPAND zero fills with L-1 zeros between each sample
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stem(x, y, linetype)
STEM Plot discrete-time sequence data.
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striplot(x, fs, n, ntick, xma...
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striplot(x, fs, n, ntick, xma...
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striplot(x, fs, n, ntick, xma...
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tonegen(digits, scale, yint)
TONEGEN generate "mystery" signal containing tones
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tonegen(digits, scale, yint)
TONEGEN generate "mystery" signal containing tones
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tonegen(digits, scale, yint)
TONEGEN generate "mystery" signal containing tones
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waterfall(x, scale)
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waterfall(x, scale)
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waterfall(x, scale)
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welch(x, N, M, wintype, nplot)
WELCH Power Spectrum Estimation by Welch's method
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welch(x, N, M, wintype, nplot)
WELCH Power Spectrum Estimation by Welch's method
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wp(x, scale)
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wp(x, scale)
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wp(x, scale)
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zerofill(X_in, L)
Zerofill is the "expander" operation used in multi-rate filters
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zplane(z, p, zmax)
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zzplane(z, p, zmax)
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zzplane(z, p, zmax)
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test_rad.m
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test_rad.m
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View all files
Computer-Based Exercises for Signal Processing Using MATLAB 5
by James McClellan
20 Aug 2002
(Updated 21 Nov 2002)
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| File Information |
| Description |
Focusing on MATLAB 5, this book includes a collection of computer exercises and projects that helps students understand the principles of signal processing and experience the excitement of applying abstract mathematical concepts to the processing of real signals.
For a full book description and ordering information, please refer to http://www.mathworks.com/support/books/book1484.jsp. |
| MATLAB release |
MATLAB 5.2 (R10)
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