Transmission of array data by multivariate convolution and cross-correlation using white-noise reference signal

An information-transmission scheme with holographic-like properties is described for encoding and decoding multidimensional imagery data. An m-dimensional message pattern is mapped into an mth order Wiener kernel, creating a non-linear system. The sender stimulates this system with a gaussian white-...

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Vydáno v:International Journal of Systems Science Ročník 15; číslo 5; s. 525 - 541
Hlavní autoři: YASUI, SYOZO, KOBLASZ, ARTHUR
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Taylor & Francis Group 01.05.1984
Informa UK Limited
Taylor & Francis
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ISSN:0020-7721, 1464-5319
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Abstract An information-transmission scheme with holographic-like properties is described for encoding and decoding multidimensional imagery data. An m-dimensional message pattern is mapped into an mth order Wiener kernel, creating a non-linear system. The sender stimulates this system with a gaussian white-noise input and the response is transmitted to the receiving end. Thus, the encoding algorithm is a convolutional operation. The white-noise input serves as a reference signal which may be also transmitted, or alternatively may be conveyed a priori to the intended receiver. The message pattern is decoded by performing an m -dimensional cross-correlation between the stimulus and response signals. The method is particularly suitable when the transmission is subject to severe extraneous noise disturbances including periods of complete signal loss. This is demonstrated by making comparisons with the photographic telecommunication operating on a point-by-point basis, as well as through a computer-simulated example.
AbstractList An information-transmission scheme with holographic-like properties is described for encoding and decoding multidimensional imagery data. An m-dimensional message pattern is mapped into an mth order Wiener kernel, creating a non-linear system. The sender stimulates this system with a gaussian white-noise input and the response is transmitted to the receiving end. Thus, the encoding algorithm is a convolutional operation. The white-noise input serves as a reference signal which may be also transmitted, or alternatively may be conveyed a priori to the intended receiver. The message pattern is decoded by performing an m-dimensional cross-correlation between the stimulus and response signals. The method is particularly suitable when the transmission is subject to severe extraneous noise distrubances including periods of complete signal loss.
An information-transmission scheme with holographic-like properties is described for encoding and decoding multidimensional imagery data. An m-dimensional message pattern is mapped into an mth order Wiener kernel, creating a non-linear system. The sender stimulates this system with a gaussian white-noise input and the response is transmitted to the receiving end. Thus, the encoding algorithm is a convolutional operation. The white-noise input serves as a reference signal which may be also transmitted, or alternatively may be conveyed a priori to the intended receiver. The message pattern is decoded by performing an m -dimensional cross-correlation between the stimulus and response signals. The method is particularly suitable when the transmission is subject to severe extraneous noise disturbances including periods of complete signal loss. This is demonstrated by making comparisons with the photographic telecommunication operating on a point-by-point basis, as well as through a computer-simulated example.
Author YASUI, SYOZO
KOBLASZ, ARTHUR
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SubjectTerms Adaptative systems
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Title Transmission of array data by multivariate convolution and cross-correlation using white-noise reference signal
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