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Guest Editorial Learning in Neuromorphic Systems and Cyborg Intelligence

Zhaohui Wu, Ryad Benosman, Huajin Tang, Shih-Chii Liu
2017 IEEE Transactions on Neural Networks and Learning Systems  
The third paper, entitled A binaural neuromorphic auditory sensor for FPGA: A spike signal processing approach, presents a new architecture, design flow, and FPGA implementation of a neuromorphic binaural  ...  This paper also presents a 64 channel binaural neuromorphic auditory system implemented in a Virtex-5 FPGA using a commercial development board.  ...  Benosman was awarded with the National Best French Scientific Paper by the Journal La Recherche for his work on neuromorphic retinas and their applications to retina stimulation and prosthetics in 2013  ... 
doi:10.1109/tnnls.2017.2650599 fatcat:ww34h4veofg6zky6w76mtlqkke

Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review

Mohammad-Hassan Tayarani-Najaran, Michael Schmuker
2021 Frontiers in Neural Circuits  
We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities.  ...  The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches to sensing and signal processing.  ...  AUTHOR CONTRIBUTIONS Both authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.  ... 
doi:10.3389/fncir.2021.610446 pmid:34135736 pmcid:PMC8203204 fatcat:qjvv6czzufazthcyvs7go5pnj4

A Comparison of Low-Complexity Real-Time Feature Extraction for Neuromorphic Speech Recognition

Jyotibdha Acharya, Aakash Patil, Xiaoya Li, Yi Chen, Shih-Chii Liu, Arindam Basu
2018 Frontiers in Neuroscience  
This paper presents a real-time, low-complexity neuromorphic speech recognition system using a spiking silicon cochlea, a feature extraction module and a population encoding method based Neural Engineering  ...  Hardware measurements for the same topology show a slightly reduced accuracy of 94% that can be attributed to the extra correlations in hardware random weights.  ...  Though the entire processing of the signal does not use spike times, our method still uses "physical" computation in the cochlea and NEF/ELM blocks which is the essence of neuromorphic engineering as described  ... 
doi:10.3389/fnins.2018.00160 pmid:29643760 pmcid:PMC5882819 fatcat:4by2b7ytxfg2zlgmilm6hnfveu

Breaking the millisecond barrier on SpiNNaker: implementing asynchronous event-based plastic models with microsecond resolution

Xavier Lagorce, Evangelos Stromatias, Francesco Galluppi, Luis A. Plana, Shih-Chii Liu, Steve B. Furber, Ryad B. Benosman
2015 Frontiers in Neuroscience  
Spike-based neuromorphic sensors such as retinas and cochleas, change the way in which the world is sampled.  ...  neuromorphic sensors.  ...  The work proposed in this paper results from discussions at the Telluride Neuromorphic Cognition Engineering Workshop; the authors would like to thank the sponsors and the organizers.  ... 
doi:10.3389/fnins.2015.00206 pmid:26106288 pmcid:PMC4458614 fatcat:j7wfasjaxzhfrmdolfob3wxomm

Bayesian Estimation and Inference Using Stochastic Electronics

Chetan Singh Thakur, Saeed Afshar, Runchun M. Wang, Tara J. Hamilton, Jonathan Tapson, André van Schaik
2016 Frontiers in Neuroscience  
The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online  ...  In this implementation, sensors make noisy observations of the target position at discrete time steps.  ...  AUTHOR CONTRIBUTIONS All authors listed, have made substantial, direct and intellectual contribution to the work, and approved it for publication.  ... 
doi:10.3389/fnins.2016.00104 pmid:27047326 pmcid:PMC4796016 fatcat:75sajr2l3fhz7m7jhq54cmtxre

Massive MIMO functionality splits based on hybrid analog-digital precoding in a C-RAN architecture

Dong Min Kim, Jihong Park, Elisabeth De Carvalho, Carles Navarro Manchon
2017 2017 51st Asilomar Conference on Signals, Systems, and Computers  
In this talk, I explain why communication at millimeter wave -and even higher frequencies -is interesting from a signal processing perspective.  ...  I describe the signal processing challenges associated with fast antenna array configuration.  ...  (Invited) WA5b Array Signal Processing Algorithms WA6a Signal Processing for Hearing Aids (Invited) WA6b Neural Signal Processing WA7a Hardware Design for Machine Learning (Invited) WA7b Video Processing  ... 
doi:10.1109/acssc.2017.8335612 dblp:conf/acssc/KimPCM17 fatcat:jujepkjavrftfdg2w7ooy3lucy

Sparsely Activated Networks: A new method for decomposing and compressing data [article]

Paschalis Bizopoulos
2021 arXiv   pre-print
We lastly present Sparsely Activated Networks (SANs) that consist of kernels with shared weights that, during encoding, are convolved with the input and then passed through a sparse activation function  ...  We compare SANs using the five previously defined activation functions on a variety of datasets (Physionet, UCI-epilepsy, MNIST, FMNIST) and show that models that are selected using φ have small description  ...  A binaural neuromorphic auditory sensor for fpga: A spike signal processing approach. IEEE Trans. Neural Netw.  ... 
arXiv:1911.00400v2 fatcat:4gdsy2iywvgitdugodkdfqdzg4

Sparsely Activated Networks: A new method for decomposing and compressing data [article]

Paschalis Bizopoulos, National Technological University Of Athens, National Technological University Of Athens
2020
A binaural neuromorphic auditory sensor for fpga: A spike signal processing approach. IEEE Trans. Neural Netw.  ...  Deep neural networks for the recognition and classification of heart murmurs using neuromorphic auditory sensors.  ...  i = 1 to q do 2: 3: end for 4: for e = 1 to epochs do 5: for b = 1 to batches do 6: x (b) ∼ x 7: for i = 1 to q do 8: 10: 15:  ... 
doi:10.26240/heal.ntua.17607 fatcat:afzmycgzbjhcpgkuz56q6oj75m