The principles of convolution and deconvolution known for linear systems have been applied to many engineering problems such as electromagnetic inverse scattering, seismology, system identifications, pattern recognition, etc. For applications involving a large amount of data, systolic array processing is attractive for efficiency and reduction of the data-processing time. Systolic arrays for discrete-time convolution have been previously developed. A triangular systolic array, consisting of two types of processing cells, is presented for the discrete-time deconvolution. The functions of the processing cells and their interconnections are described. The pipeline architecture of the triangular systolic array is derived from the recursive pattern of deconvolution. Cell computations and data flow within the systolic array are synchronized by a single global clock. >
[1]
M. Ekstrom.
A spectral characterization of the ill-conditioning in numerical deconvolution
,
1973,
IEEE Transactions on Audio and Electroacoustics.
[2]
John G. McWhirter,et al.
MULTIBIT CONVOLUTION USING A BIT LEVEL SYSTOLIC ARRAY.
,
1985
.
[3]
H. T. Kung.
Why systolic architectures?
,
1982,
Computer.
[4]
Sun-Yuan Kung,et al.
On supercomputing with systolic/wavefront array processors
,
1984
.
[5]
S. Kung,et al.
VLSI Array processors
,
1985,
IEEE ASSP Magazine.
[6]
S.M. Riad,et al.
The deconvolution problem: An overview
,
1986,
Proceedings of the IEEE.