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08/09/2019
One-time learning and reverse salience signal with a salience affected neural network (SANN)
Standard artificial neural networks model key cognitive aspects of brain...
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08/09/2019
One-time learning in a biologically-inspired Salience-affected Artificial Neural Network (SANN)
Standard artificial neural networks (ANNs), loosely based on the structu...
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07/18/2019
Event-based Feature Extraction Using Adaptive Selection Thresholds
Unsupervised feature extraction algorithms form one of the most importan...
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03/14/2016
Investigation of event-based memory surfaces for high-speed tracking, unsupervised feature extraction and object recognition
In this paper we compare event-based decaying and time based-decaying me...
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03/13/2016
A Stochastic Approach to STDP
We present a digital implementation of the Spike Timing Dependent Plasti...
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09/03/2015
A Reconfigurable Mixed-signal Implementation of a Neuromorphic ADC
We present a neuromorphic Analogue-to-Digital Converter (ADC), which use...
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09/03/2015
A compact aVLSI conductance-based silicon neuron
We present an analogue Very Large Scale Integration (aVLSI) implementati...
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07/21/2015
A neuromorphic hardware architecture using the Neural Engineering Framework for pattern recognition
We present a hardware architecture that uses the Neural Engineering Fram...
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07/10/2015
A Trainable Neuromorphic Integrated Circuit that Exploits Device Mismatch
Random device mismatch that arises as a result of scaling of the CMOS (c...
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05/11/2015
An Online Learning Algorithm for Neuromorphic Hardware Implementation
We propose a sign-based online learning (SOL) algorithm for a neuromorph...
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03/02/2015
A neuromorphic hardware framework based on population coding
In the biological nervous system, large neuronal populations work collab...
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03/02/2015
FPGA Implementation of the CAR Model of the Cochlea
The front end of the human auditory system, the cochlea, converts sound ...
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12/29/2014
Fast, simple and accurate handwritten digit classification by training shallow neural network classifiers with the 'extreme learning machine' algorithm
Recent advances in training deep (multi-layer) architectures have inspir...
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08/06/2014
Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels
This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN)...
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06/12/2014
Learning ELM network weights using linear discriminant analysis
We present an alternative to the pseudo-inverse method for determining t...
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06/11/2014
Explicit Computation of Input Weights in Extreme Learning Machines
We present a closed form expression for initializing the input weights i...
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05/30/2014
ELM Solutions for Event-Based Systems
Whilst most engineered systems use signals that are continuous in time, ...
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05/30/2014
Online and Adaptive Pseudoinverse Solutions for ELM Weights
The ELM method has become widely used for classification and regressions...
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06/13/2013
The Ripple Pond: Enabling Spiking Networks to See
In this paper we present the biologically inspired Ripple Pond Network (...
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07/13/2012
