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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2
Hardware Implementation of a PCA Learning Network by an Asynchronous PDM Digital Circuit
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
Yuzo Hirai, University of Tsukuba
Kuninori Nishizawa, University of Tsukuba
We have fabricated a PCA (Principal Component Analysis) learning network in a FPGA (Field Programmable Gate Array) b y using an asynchronous PDM (Pulse Density Modulation) digital circuit. The generalized Hebbian algorithm is expressed in a set of ordinary differential equations and the circuits solve them in a parallel and continuous manner. A network with two-microphone inputs and two-speaker outputs tested the performance of the circuits. By moving a sound source right and left in front of the microphones, the first principal weight vector could continuously track the sound direction in real time.
Citation:
Yuzo Hirai, Kuninori Nishizawa, "Hardware Implementation of a PCA Learning Network by an Asynchronous PDM Digital Circuit," ijcnn, vol. 2, pp.2065, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 2, 2000
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