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A neural implementation of the JADE algorithm using higher-order neurons

Ziegaus, Ch. ; Lang, Elmar



Abstract

A neural implementation of the JADE algorithm, called nJADE, is developed which adaptively determines the mixing matrices to be jointly diagonalized with the JADE algorithm. This alleviates the problem of algebraically determining these mixing matrices which becomes a very tedious if not impossible undertaking with high dimensional data. The new learning rule uses higher-order neurons ...

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