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• W2564594331 abstract "A field-programmable gate array (FPGA)-based speech measurement and recognition system is the focus of this paper, and the environmental noise problem is its main concern. To accelerate the recognition speed of the FPGA-based speech recognition system. Furthermore, the empirical mode decomposition is used to decompose the measured speech signal contaminated by noise into several intrinsic mode functions (IMFs). The IMFs are then weighted and summed to reconstruct the original clean speech signal. Unlike previous research, in which IMFs were selected by trial and error for specific applications, the weights for each IMF are designed by the genetic algorithm to obtain an optimal solution." @default.
• W2564594331 created "2017-01-06" @default.
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• W2564594331 date "2015-01-01" @default.
• W2564594331 modified "2023-10-18" @default.
• W2564594331 title "FPGA Implementation of Optimized Spiking Neural Network for Efficient Speak recognition System" @default.
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• W2564594331 doi "https://doi.org/10.51976/ijari.311518" @default.
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