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09/20/2023
Limitations in odour recognition and generalisation in a neuromorphic olfactory circuit
Neuromorphic computing is one of the few current approaches that have th...
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06/10/2023
RAMAN: A Re-configurable and Sparse tinyML Accelerator for Inference on Edge
Deep Neural Network (DNN) based inference at the edge is challenging as ...
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05/31/2023
Efficient Implementation of a Multi-Layer Gradient-Free Online-Trainable Spiking Neural Network on FPGA
This paper presents an efficient hardware implementation of the recently...
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12/14/2022
Event-driven Spectrotemporal Feature Extraction and Classification using a Silicon Cochlea Model
This paper presents a reconfigurable digital implementation of an event-...
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09/27/2021
An optimised deep spiking neural network architecture without gradients
We present an end-to-end trainable modular event-driven neural architect...
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05/13/2021
Superevents: Towards Native Semantic Segmentation for Event-based Cameras
Most successful computer vision models transform low-level features, suc...
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10/22/2020
Source localization using particle filtering on FPGA for robotic navigation with imprecise binary measurement
Particle filtering is a recursive Bayesian estimation technique that has...
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11/20/2019
Event-based Object Detection and Tracking for Space Situational Awareness
In this work, we present optical space imaging using an unconventional y...
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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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07/16/2019
Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems
Batch-normalization (BN) layers are thought to be an integrally importan...
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12/07/2018
Star Tracking using an Event Camera
Star trackers are primarily optical devices that are used to estimate th...
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05/23/2018
Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain
Neuromorphic engineering (NE) encompasses a diverse range of approaches ...
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03/08/2018
An FPGA-based Massively Parallel Neuromorphic Cortex Simulator
This paper presents a massively parallel and scalable neuromorphic corte...
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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