3 research outputs found

    Neural networks : analog VLSI implementation and learning algorithms

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    Using Coherent Pulse Width and Edge Modulations in Artificial Neural Systems

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    This paper describes an existing silicon implementation of an artificial neural system based on coherent pulse width and edge modulation techniques. A chip set with different neural functions has been conceived, manufactured and tested. Neural circuits have been optimized for lowest computation energy and highest reconfigurability. The main device is a 32 × 32 synaptic array consuming 10 mW of power at 140 MCPS. Synapsis size is about 7.200 μm2 using a standard 1.5 μm CMOS technology. The problem of interfacing robotic sensors and actuators is addressed: voltage, current and resistance-based sensors are considered for the measurement of physical quantities such as temperature, pressure, strain, etc. Low resolution imaging sensors for robotic vision are also considered

    Implementing radial basis function neural networks in pulsed analogue VLSI

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