Sufficient conditions for stability are obtained for feedback systems containing a single time-varying nonlinear element whose input-output characteristic lies within a finite sector. An improved frequency-domain crit...
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Sufficient conditions for stability are obtained for feedback systems containing a single time-varying nonlinear element whose input-output characteristic lies within a finite sector. An improved frequency-domain criterion is developed. This criterion utilizes information related to the rate at which the output of the nonlinearity varies with time. Examples are provided to demonstrate the particular advantages of the improved criterion.
The purpose of this paper is to present a simple template-matching pattern recognition technique by using any general-purpose associative memory. The input patterns for recognition may have wide variations, provided t...
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The purpose of this paper is to present a simple template-matching pattern recognition technique by using any general-purpose associative memory. The input patterns for recognition may have wide variations, provided that the distinct features of individual pattern classes can be extracted. Each pattern class is allowed to have deviations in size, style, orientation, etc. within certain limits. This pattern recognition technique is extremely efficient in handwritten character recognition, which is used for illustration in this paper. Because each input pattern is processed with all the pattern classes simultaneously, the speed of this pattern recognition technique is very high. It is found that most input patterns are recognized within first comparison process and no input patterns require more than two comparison processes for their recognition.
This paper describes how an adaptive system can adapt itself to optimize its performance under the influence of uncertain environment. At each stage of adaptation, the uncertain environment, which is represented by a ...
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This paper describes how an adaptive system can adapt itself to optimize its performance under the influence of uncertain environment. At each stage of adaptation, the uncertain environment, which is represented by a random vector with an unknown statistical property, is estimated by Bayesian approach from its past outcomes up to the latest one. This approach is investigated in general so that the probability distribution of the future outcomes of the random vector is not restricted to any particular one. For most of the adaptive systems, these probability distributions are assumed to be the same. However, in the case of signal adaptation, it is shown that the results as well as the execution of the optimization technique are alike whether or not the probability distributions of the forthcoming outcomes of the random vector are the same.
In this paper, a new class of error-correcting linear block codes using symbols from GF(2 m ) is presented. These codes are not cyclic codes, but posses instead a unique algebraic structure. It is shown that they are ...
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In this paper, a new class of error-correcting linear block codes using symbols from GF(2 m ) is presented. These codes are not cyclic codes, but posses instead a unique algebraic structure. It is shown that they are instantaneously decodable with a modest amount of hardware consisting almost entirely of mod 2 adders for correcting burst errors. Furthermore, their efficiency compares favorably with the Varsharmov-Gilbert bound for both random errors over GF(2 m ) and burst errors over GF(2).
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