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Ranking or ordering of a set of numbers based on their relative magnitudes is a fundamental operation in computing. In this paper, we propose a neural circuit for ranking a given set of numbers. The proposed network does not require any feedback connection, requires fewer neurons, and fewer interconnections between neurons as compared to existing schemes. Moreover, the numbers to be sorted are applied...
A novel current-mode neural circuit employing non-linear feedback to solve a system of simultaneous linear equations is presented. The circuit has an associated transcendental energy function that ensures fast convergence to the exact solution while enjoying a resistor-less implementation. The hardware complexity of the proposed scheme compares favourably with existing voltage-mode neural circuits...
A feedback neural network based CMOS compatible circuit to solve a system of simultaneous linear equations is presented. The circuit has an associated transcendental energy function that ensures fast convergence to the exact solution while enjoying reduction in hardware complexity over existing schemes. HSPICE simulation results are presented for a chosen set of equations and are found to agree exactly...
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