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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
Search results
Showing 381 to 390 of 1665 (0.108 seconds)Spelling suggestions: "subject:"forminformation 1heory"" "subject:"forminformation atheory""
| 381 |
A parallel architecture for multimedia communicationsChng, Raymond S. K. January 1993 (has links)
No description available.
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| 382 |
Low bit-rate speech coding : A parallel processing approach using digital signal processorsChan, C. F. January 1986 (has links)
No description available.
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| 383 |
Optimal decoding for line codesAbdulwahid, Khalid January 1990 (has links)
No description available.
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| 384 |
Television standards conversionBorer, Tim January 1992 (has links)
No description available.
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| 385 |
Mobile data communication via leaky feedersMotley, A. J. January 1981 (has links)
No description available.
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| 386 |
Sinusoidal model based low bit rate speech coding for communication systemsYeldener, Suat January 1993 (has links)
No description available.
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| 387 |
Investigation of the theory and implementation of adaptive recursive second order polynomial filtersRoy, Emmanuel January 1996 (has links)
No description available.
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| 388 |
Artificial neural networks for digital signal processing applicationsJha, Sanjay Kumar January 1990 (has links)
No description available.
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| 389 |
Wavelet transform based image and video codingGoh, Kwong Huang January 1994 (has links)
No description available.
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| 390 |
Statistical approach toward designing expert systemHu, Zhiji January 1988 (has links)
Inference under uncertainty plays a crucial role in expert system and receives growing attention from artificial intelligence experts, statisticians, and psychologists. In searching for new satisfactory ways to model inference under uncertainty, it will be necessary to combine the efforts of researchers from different areas. It is expected that with deep insight into this crucial problem, it will not only have enormous impact on development of AI and expert system, but also bring classical areas like statistics into a new stage. This research paper gives a precise synopsis of present work in the field and explores the mechanics of statistical inference to a new depth by combining efforts of computer scientists, statisticians, and psychologists. One important part of the paper is the comparison of different paradigms, including the difference between statistical and logical views. Special attentions, which need to be paid when combining various methods, are considered in the paper. Also, some examples and counterexamples will be given to illustrate the availability of individual model which describes human behavior. Finally, a new framework to deal with uncertainty is proposed, and future trends of uncertainty management are projected. / Department of Mathematical Sciences
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