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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 1950s. [3]
Among his other major written works is the book Symbolic and Knowledge-Based Signal Processing [12] at the intersection of signal processing and artificial intelligence research, as well as the textbook Signals and Systems [13] that he co-authored with Alan V. Oppenheim and Alan S. Willsky.
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.
The FIR convolution is a cross-correlation between the input signal and a time-reversed copy of the impulse response. Therefore, the matched filter's impulse response is "designed" by sampling the known pulse-shape and using those samples in reverse order as the coefficients of the filter.
A related window function is the Kaiser–Bessel-derived (KBD) window, which is designed to be suitable for use with the modified discrete cosine transform (MDCT). The KBD window function is defined in terms of the Kaiser window of length N+1, by the formula:
In digital signal processing, downsampling, compression, and decimation are terms associated with the process of resampling in a multi-rate digital signal processing system. Both downsampling and decimation can be synonymous with compression , or they can describe an entire process of bandwidth reduction ( filtering ) and sample-rate reduction.
Anticausal systems are also acausal, but the converse is not always true. An acausal system that has any dependence on past input values is not anticausal. An example of acausal signal processing is the production of an output signal that is processed from an input signal that was recorded by looking at input values both forward and backward in ...