Zobrazeno 1 - 10
of 244
pro vyhledávání: '"Tapson, Jonathan"'
Autor:
Christensen, Dennis V., Dittmann, Regina, Linares-Barranco, Bernabé, Sebastian, Abu, Gallo, Manuel Le, Redaelli, Andrea, Slesazeck, Stefan, Mikolajick, Thomas, Spiga, Sabina, Menzel, Stephan, Valov, Ilia, Milano, Gianluca, Ricciardi, Carlo, Liang, Shi-Jun, Miao, Feng, Lanza, Mario, Quill, Tyler J., Keene, Scott T., Salleo, Alberto, Grollier, Julie, Marković, Danijela, Mizrahi, Alice, Yao, Peng, Yang, J. Joshua, Indiveri, Giacomo, Strachan, John Paul, Datta, Suman, Vianello, Elisa, Valentian, Alexandre, Feldmann, Johannes, Li, Xuan, Pernice, Wolfram H. P., Bhaskaran, Harish, Furber, Steve, Neftci, Emre, Scherr, Franz, Maass, Wolfgang, Ramaswamy, Srikanth, Tapson, Jonathan, Panda, Priyadarshini, Kim, Youngeun, Tanaka, Gouhei, Thorpe, Simon, Bartolozzi, Chiara, Cleland, Thomas A., Posch, Christoph, Liu, Shih-Chii, Panuccio, Gabriella, Mahmud, Mufti, Mazumder, Arnab Neelim, Hosseini, Morteza, Mohsenin, Tinoosh, Donati, Elisa, Tolu, Silvia, Galeazzi, Roberto, Christensen, Martin Ejsing, Holm, Sune, Ielmini, Daniele, Pryds, N.
Publikováno v:
Neuromorph. Comput. Eng. 2 022501 (2022)
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This dat
Externí odkaz:
http://arxiv.org/abs/2105.05956
In this paper we introduce a novel Salience Affected Artificial Neural Network (SANN) that models the way neuromodulators such as dopamine and noradrenaline affect neural dynamics in the human brain by being distributed diffusely through neocortical
Externí odkaz:
http://arxiv.org/abs/1908.03532
Unsupervised feature extraction algorithms form one of the most important building blocks in machine learning systems. These algorithms are often adapted to the event-based domain to perform online learning in neuromorphic hardware. However, not desi
Externí odkaz:
http://arxiv.org/abs/1907.07853
The MNIST dataset has become a standard benchmark for learning, classification and computer vision systems. Contributing to its widespread adoption are the understandable and intuitive nature of the task, its relatively small size and storage require
Externí odkaz:
http://arxiv.org/abs/1702.05373
In this paper we compare event-based decaying and time based-decaying memory surfaces for high-speed eventbased tracking, feature extraction, and object classification using an event-based camera. The high-speed recognition task involves detecting an
Externí odkaz:
http://arxiv.org/abs/1603.04223
Autor:
Wang, Runchun, Thakur, Chetan Singh, Hamilton, Tara Julia, Tapson, Jonathan, van Schaik, André
We present a digital implementation of the Spike Timing Dependent Plasticity (STDP) learning rule. The proposed digital implementation consists of an exponential decay generator array and a STDP adaptor array. On the arrival of a pre- and post-synapt
Externí odkaz:
http://arxiv.org/abs/1603.04080
Autor:
Xu, Ying, Thakur, Chetan Singh, Hamilton, Tara Julia, Tapson, Jonathan, Wang, Runchun, van Schaik, Andre
We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) neurons as the encoders of the analogue signal, with modulated inhibitions to decohere the neuronal spikes trains. The architecture consists of an anal
Externí odkaz:
http://arxiv.org/abs/1509.00967
Autor:
Wang, Runchun, Thakur, Chetan Singh, Hamilton, Tara Julia, Tapson, Jonathan, van Schaik, Andre
We present an analogue Very Large Scale Integration (aVLSI) implementation that uses first-order lowpass filters to implement a conductance-based silicon neuron for high-speed neuromorphic systems. The aVLSI neuron consists of a soma (cell body) and
Externí odkaz:
http://arxiv.org/abs/1509.00962
Autor:
Wang, Runchun, Thakur, Chetan Singh, Hamilton, Tara Julia, Tapson, Jonathan, van Schaik, Andre
We present a hardware architecture that uses the Neural Engineering Framework (NEF) to implement large-scale neural networks on Field Programmable Gate Arrays (FPGAs) for performing pattern recognition in real time. NEF is a framework that is capable
Externí odkaz:
http://arxiv.org/abs/1507.05695
Autor:
Thakur, Chetan Singh, Wang, Runchun, Hamilton, Tara Julia, Tapson, Jonathan, van Schaik, Andre
Random device mismatch that arises as a result of scaling of the CMOS (complementary metal-oxide semi-conductor) technology into the deep submicron regime degrades the accuracy of analogue circuits. Methods to combat this increase the complexity of d
Externí odkaz:
http://arxiv.org/abs/1507.02835