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MONTETULL Associate ProfessorABSTRACT Prediction is a VpicaI example of a generalization problem. The goal of prediction is to accurately forecast the short-term evolution of the system based on past information. Neural network andfirzzy logic techniques are used because they both have good generalization capabilities. The embedding dimension (number of inputs) and the time lag selection problem is treated in this paper. It is proposed, that the selection of the appropriate embedding dimension and time lag for the inpudoutput space construction pkzys an important role in the perfrmance of the above networh. It is shown that the "traditionally accepted" choices for the embedding dimension and time lag are not optimal. The proposed method ofers an improvement over the traditionally accepted parameter choices. Direrent analytical techniques for the determination of these parameters are used, and the results are evaluated.
Abstr act -This paper addr esses two problems associated with the traditional appr ach to teaching a junior level course in signals and systems. First, students are exp ectedto develop facility with a variety of transforms and we have observed that this overwhelms many, reducing them to simply "memorizing equations." Second, the usual treatment of Dir ac'sdelta as a function not only leads to serious contr adictions with the standard calculus, but also leaves intractable schisms surr ounding the transforms of important harmonic functions. W e present a unified and consistent approach design& to ameliorate these problems using abstract linear algebr a and distribution theory. The appr oachwas implemented for four semesters and exit surveys were conducted to assess pedago gical effetiveness.
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