8 December 1978 Signal Processing Architectures Using Convolutional Technology
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Abstract
Modem signal processing frequently requires linear transforms in both space and time, such as beamforming and temporal Fourier analysis. Such linear processing operations form a large portion of the computational load for many signal processing problems. Convolu-tional devices including transversal filters and crossconvolvers form highly parallel computations modules with high throughput and minimal control overhead. Such modules may be used not only for time-invariant linear transforms such as matched filtering and cross-convolution, but also a large class of time-variant linear transforms such as one-dimensional and two-dimensional Fourier transforms and beamformers for selected array geometries, including one-dimensional and multidimensional uniformly spaced arrays, the circular array, the power law curve array, and the exponentially spaced line array. Special architectures using uniformly tapped multiport (program-mable) convolvers are applicable to a wider set of array geometries the generalized Lissajous figure arrays. In several cases, the same architecture will accommodate a variety of array geometries by simply changing the output of a function generator. To extend these techniques to a completely arbitrary, time-varying array requires the equivalent of a multiport convolver with moveable taps. The most attractive candidate for such a device at present is a further development of the acousto-optic memory convolver.
© (1978) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jeffrey M. Speiser, Harper J. Whitehouse, Norman J. Berg, "Signal Processing Architectures Using Convolutional Technology", Proc. SPIE 0154, Real-Time Signal Processing I, (8 December 1978); doi: 10.1117/12.938240; https://doi.org/10.1117/12.938240
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