A Neuron Based Switch: Application to Low Power Mixed Signal Circuits
This work addresses power reduction in mixed-signal circuits for hardware applications, but it is incremental as it applies an existing neuron model to a specific circuit.
The paper applied a VLSI cortical neuron model, based on the Izhikevich model and spike/burst firing patterns, to a DC differential amplifier to achieve low power design in mixed-signal circuits.
Human brain is functionally and physically complex. This 'complexity' can be seen as a result of biological design process involving extensive use of concepts such as modularity and hierarchy. Over the past decade, deeper insights into the functioning of cortical neurons have led to the development of models that can be implemented in hardware. The implementation of biologically inspired spiking neuron networks in silicon can provide solutions to difficult cognitive tasks. The work reported in this paper is an application of a VLSI cortical neuron model for low power design. The VLSI implementation shown in this paper is based on the spike and burst firing pattern of cortex and follows the Izhikevich neuron model. This model is applied to a DC differential amplifier as practical application of power reduction