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Driver Filter Design for Software-Implemented Loudspeaker Crossovers

100%

Yao S. N.

tom Vol. 39, No. 4

591--597

A hybrid method is presented for the integration of low-, mid-, and high-frequency driver filters in loud- speaker crossovers. The Pascal matrix is exploited to calculate denominators; the locations of minimum values in frequency magnitude responses are associated with the forms of numerators; the maximum values are used to compute gain factors. The forms of the resulting filters are based on the physical meanings of low-pass, band-pass, and high-pass filters, an intuitive idea which is easy to be understood. Moreover, each coefficient is believed to be simply calculated, an advantage which keeps the software- implemented crossover running smoothly even if crossover frequencies are being changed in real time. This characteristic allows users to efficiently adjust the bandwidths of the driver filters by subjective listening tests if objective measurements of loudspeaker parameters are unavailable. Instead of designing separate structures for a low-, mid-, and high-frequency driver filter, by using the proposed techniques we can implement one structure which merges three types of digital filters. Not only does the integra- tion architecture operate with low computational cost, but its size is also compact. Design examples are included to illustrate the effectiveness of the presented methodology.

Application of genetic algorithmbin an active noise control system

100%

Makarewicz G.

tom Vol. 32, No. 4

839--849

An active noise control (ANC) system utilizing a genetic algorithm for reduction of noise in duct is described. A continuous genetic algorithm with a heuristic crossover method was applied in the controller of the system. The ANC system was tested on a laboratory stand. Measurements of the efficiency of the system related to basic parameters of the genetic algorithm were performed. A comparison of the effectiveness of ANC system based on the genetic algorithm to the system based on the LMS algorithm is presented.

Optimization of induction motor design

86%

Sames M.

Zeszyty Naukowe. Elektryka / Politechnika Śląska

2001

tom z. 176

103-110

The problem with electric machine optimization can be specified as searching for a compromise between requirements manufacturer's and user's. Optimum design depends on several parameters, therefore it is very difficult fo find real optimum. The evolutionary methods seem to be a way to solve this problem. In this paper there is explained the basic principle of simple Genetic algorithm with binary coding and Simulated Annealing algorithm. Their application to design optimization of a maximum efficiency induction motor is presented as well.

The generating new individuals of the population in the parametric identification of the induction motor problem with the use of the genetic algorithm

72%

Rutczyńska-Wdowiak K.

tom Vol. 116, iss. 2

109--117

This paper presents the problem of the identifying parameters for use in mathematical models of induction motors with the use of a genetic algorithm (GA). The effect of arithmetical crossover and the generation of new populations on identification results is analysed. The identified parameters of the model were determined as a result of the minimisation of the performance index defined as the mean-square error of stator current and angular velocity. The experiments were performed for the low power induction motor. The steady-state genetic algorithm with regard to convergence and accuracy of the identification process and calculation time is analysed.

W artykule przedstawiono problem identyfikacji parametrów modeli matematycznych silników indukcyjnych z zastosowaniem algorytmu genetycznego (AG). Analizowano wpływ krzyżowania arytmetycznego i generowania potomków na wyniki identyfikacji. Identyfikowane parametry modelu wyznaczono w rezultacie minimalizacji wskaźnika jakości zdefiniowanego jako błąd średniokwadratowy prądu stojana i prędkości kątowej. Badania eksperymentalne przeprowadzono dla silnika indukcyjnego małej mocy. Algorytm genetyczny z częściową wymianą populacji analizowano ze względu na zbieżność i dokładność procesu identyfikacji i czas obliczeń numerycznych.

Driver Filter Design for Software-Implemented Loudspeaker Crossovers

58%

Yao S.-N.

nr 4