An event coded configurable analog circuit block that forms the building block of a programmable analog array is presented. The de- sign of the event block is inspired from the behavior of biological neurons that process signals in analog domain and transmit them as spike events. In the configurable event block implemented here, no events are trans- mitted when the signals are relatively constant thereby leading to lower energy dissipation and better utilization of resources in analog arrays. The block diagram and the circuit schematics of the event coded configurable analog block are described. Application examples are presented to demonstrate the reconfigurability and functionality of the event coded circuit block
<div>With the advent of new technologies and advancement in medical science we are trying to process...
We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) n...
We present a low energy-barrier magnet based compact hardware unit for analog stochastic neurons (AS...
A generic programmable time event coded circuit which forms the building block for a reconfigurable ...
A generic programmable spike-timing based circuit which forms the building block of a reconfigurable...
This paper presents the computation properties of an asynchronous spike event coding scheme employed...
This work is the result of the definition, design and evaluation of a novel method to interconnect t...
This paper presents a CMOS circuit implementation of a spike event coding/decoding scheme for transm...
Kaulmann T, Ferber M, Witkowski U, Rückert U. Analog VLSI Implementation of Adaptive Synapses in Pul...
We have used analog VLSI technology to model a class of biological neural circuits known as central ...
This work addresses neural and analog computation on reconfigurable mixed-signal platforms. Many eng...
computation in analog VLSI without precise synaptic weights Abstract — Recent studies demonstrated t...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
Reinforcement learning is important for machine-intelligence and neurophysiological modelling applic...
Recent studies demonstrated that sophisticated information processing can occur in spike-based compu...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) n...
We present a low energy-barrier magnet based compact hardware unit for analog stochastic neurons (AS...
A generic programmable time event coded circuit which forms the building block for a reconfigurable ...
A generic programmable spike-timing based circuit which forms the building block of a reconfigurable...
This paper presents the computation properties of an asynchronous spike event coding scheme employed...
This work is the result of the definition, design and evaluation of a novel method to interconnect t...
This paper presents a CMOS circuit implementation of a spike event coding/decoding scheme for transm...
Kaulmann T, Ferber M, Witkowski U, Rückert U. Analog VLSI Implementation of Adaptive Synapses in Pul...
We have used analog VLSI technology to model a class of biological neural circuits known as central ...
This work addresses neural and analog computation on reconfigurable mixed-signal platforms. Many eng...
computation in analog VLSI without precise synaptic weights Abstract — Recent studies demonstrated t...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
Reinforcement learning is important for machine-intelligence and neurophysiological modelling applic...
Recent studies demonstrated that sophisticated information processing can occur in spike-based compu...
<div>With the advent of new technologies and advancement in medical science we are trying to process...
We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) n...
We present a low energy-barrier magnet based compact hardware unit for analog stochastic neurons (AS...