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Ronald W. Schafer (born February 17, 1938) is an American electrical engineer notable for his contributions to digital signal processing.. After receiving his Ph.D. degree at Massachusetts Institute of Technology in 1968, he joined the Acoustics Research Department at Bell Laboratories, where he did research on digital signal processing and digital speech coding.
Alan Victor Oppenheim [2] (born 1937) is a professor of engineering at MIT's Department of Electrical Engineering and Computer Science. He is also a principal investigator in MIT's Research Laboratory of Electronics (RLE), at the Digital Signal Processing Group. His research interests are in the general area of signal processing and its ...
According to Alan V. Oppenheim and Ronald W. Schafer, the principles of signal processing can be found in the classical numerical analysis techniques of the 17th century. . They further state that the digital refinement of these techniques can be found in the digital control systems of the 1940s and 1
The following is a pseudocode of the algorithm: (Overlap-add algorithm for linear convolution) h = FIR_filter M = length(h) Nx = length(x) N = 8 × 2^ceiling( log2(M) ) (8 times the smallest power of two bigger than filter length M.
Homomorphic filtering has been used to remove the effect of the stochastic impulse train, which originates the sEMG signal, from the power spectrum of the sEMG signal itself. In this way, only information about motor unit action potential (MUAP) shape and amplitude was maintained; this was then used to estimate the parameters of a time-domain ...
Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space ...
In signal processing, a shift invariant system is the discrete equivalent of a time-invariant system, ... Oppenheim, Schafer, Digital Signal Processing, ...
The quefrency is a measure of time, though not in the sense of a signal in the time domain. For example, if the sampling rate of an audio signal is 44100 Hz and there is a large peak in the cepstrum whose quefrency is 100 samples, the peak indicates the presence of a fundamental frequency that is 44100/100 = 441 Hz.