| 摘要 |
A k-WTA circuit for selecting inputs which have a maximum-magnitude and outputting the results. k-WTA is very useful in pattern classification such as k-nearest neighbor classifier, Hamming neural classifier and some cascaded classification systems, since one classifier can not achieve very high performance, however, if a small set of candidates can be provided, for example k(k<<N), then a simple classifier with small complementary feature sets can be cascaded to realize multi-stage classification. A k-WTA network is necessary to implement this function. The circuit as disclosed in the invention provides a design for a circuit in which the number of inputs with maximum magnitudes at any one time can be chosen. The circuit can have a plurality of inputs each of which has a corresponding output. In one embodiment of the invention external inputs can select the number of maximum-magnitudes inputs to be selected through the use of a current positive feedback loop. Depending on the number of maximum-magnitude inputs selected the circuit will output voltage levels on the outputs that correspond to inputs whose current levels have higher magnitudes when compared to other inputs. The circuit has the further advantages of reconfigurability, self-adaptivity, low complexity, high accuracy, expandability, and a large dynamic range.
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