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Neuromorphic applications emulate the processing performed by the brain by using spikes as inputs instead of time-varying analog stimuli. Therefore, these time-varying stimuli have to be encoded into spikes, which can induce important…

Neural and Evolutionary Computing · Computer Science 2024-12-30 Ahmad El Ferdaoussi , Eric Plourde , Jean Rouat

Spike-timing dependent plasticity (STDP) is an organizing principle of biological neural networks. While synchronous firing of neurons is considered to be an important functional block in the brain, how STDP shapes neural networks possibly…

Neurons and Cognition · Quantitative Biology 2009-05-20 Yuko K. Takahashi , Hiroshi Kori , Naoki Masuda

A new score function is proposed for stack decoding of polar codes, which enables one to accurately compare paths of different lengths. The proposed score function includes bias, which reflects the average behaviour of the correct path.…

Information Theory · Computer Science 2018-01-16 Peter Trifonov , Vera Miloslavskaya , Ruslan Morozov

The compute-and-forward (CoF) is a relaying protocol, which uses algebraic structured codes to harness the interference and remove the noise in wireless networks. We propose the use of phase precoders at the transmitters of a network, where…

Information Theory · Computer Science 2014-09-30 Amin Sakzad , Emanuele Viterbo , Joseph Jean Boutros , Yi Hong

Elucidating the neurophysiological mechanisms underlying neural pattern formation remains an outstanding challenge in Computational Neuroscience. In this paper, we address the issue of understanding the emergence of neural patterns by…

Neurons and Cognition · Quantitative Biology 2024-06-04 Gregory Dumont , Carmen Oana Tarniceriu

The role of synchronous firing in sensory coding and cognition remains controversial. While studies, focusing on its mechanistic consequences in attentional tasks, suggest that synchronization dynamically boosts sensory processing, others…

Neurons and Cognition · Quantitative Biology 2019-05-07 Siavash Ghavami , Vahid Rahmati , Farshad Lahouti , Lars Schwabe

It has recently been recognized that the wireless networks represent a fertile ground for devising communication modes based on network coding. A particularly suitable application of the network coding arises for the two--way relay…

Information Theory · Computer Science 2007-07-13 Petar Popovski , Hiroyuki Yomo

While Spiking Neural Networks (SNNs) have been gaining in popularity, it seems that the algorithms used to train them are not powerful enough to solve the same tasks as those tackled by classical Artificial Neural Networks (ANNs). In this…

Neural and Evolutionary Computing · Computer Science 2021-10-14 Karen Adam

The coding properties of cells with different types of receptive fields have been studied for decades. ON-type neurons fire in response to positive fluctuations of the time-dependent stimulus, whereas OFF cells are driven by negative…

Neurons and Cognition · Quantitative Biology 2009-09-10 Eugenio Urdapilleta , Ines Samengo

The instantaneous state of a neural network consists of both the degree of excitation of each neuron the network is composed of and positions of impulses in communication lines between the neurons. In neurophysiological experiments, the…

Neurons and Cognition · Quantitative Biology 2013-09-10 Kseniia Kravchuk , Alexander Vidybida

We study a simple extended model of oscillator neural networks capable of storing sparsely coded phase patterns, in which information is encoded both in the mean firing rate and in the timing of spikes. Applying the methods of statistical…

Disordered Systems and Neural Networks · Physics 2009-10-31 Masaki Nomura , Toshio Aoyagi

Information coding by precise timing of spikes can be faster and more energy-efficient than traditional rate coding. However, spike-timing codes are often brittle, which has limited their use in theoretical neuroscience and computing…

Neural and Evolutionary Computing · Computer Science 2019-01-24 E. Paxon Frady , Friedrich T. Sommer

Several studies have shown that bursting neurons can encode information in the number of spikes per burst: As the stimulus varies, so does the length of individual bursts. The represented stimuli, however, vary substantially among different…

Neurons and Cognition · Quantitative Biology 2013-03-22 Inés Samengo , Germán Mato , Daniel H. Elijah , Susanne Schreiber , Marcelo A. Montemurro

The problem of serving multicast flows in a crossbar switch is considered. Intra-flow linear network coding is shown to achieve a larger rate region than the case without coding. A traffic pattern is presented which is achievable with…

Networking and Internet Architecture · Computer Science 2016-11-17 MinJi Kim , Jay Kumar Sundararajan , Muriel Medard , Atilla Eryilmaz , Ralf Koetter

This paper demonstrates the ability of neural networks to reliably learn the nonlinear flame response of a laminar premixed flame, while carrying out only one unsteady CFD simulation. The system is excited with a broadband, low-pass…

Fluid Dynamics · Physics 2022-04-12 Nilam Tathawadekar , Nguyen Anh Khoa Doan , Camilo F. Silva , Nils Thuerey

The training of multilayer spiking neural networks (SNNs) using the error backpropagation algorithm has made significant progress in recent years. Among the various training schemes, the error backpropagation method that directly uses the…

Neural and Evolutionary Computing · Computer Science 2023-07-26 Yusuke Sakemi , Kakei Yamamoto , Takeo Hosomi , Kazuyuki Aihara

We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep…

Quantum Physics · Physics 2017-07-20 Giacomo Torlai , Roger G. Melko

Zipper codes are a framework for describing spatially-coupled product-like codes. Many well-known codes, such as staircase codes and braided block codes, are subsumed into this framework. New types of codes such as tiled diagonal and…

Information Theory · Computer Science 2024-10-31 Alvin Y. Sukmadji , Umberto Martínez-Peñas , Frank R. Kschischang

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last twenty…

Neurons and Cognition · Quantitative Biology 2018-05-15 David Papo

Two elements of neural information processing have primarily been proposed: firing rate and spike timing of neurons. In the case of synaptic plasticity, although spike-timing-dependent plasticity (STDP) depending on presynaptic and…

Neurons and Cognition · Quantitative Biology 2020-01-14 Katsuhiko Hata , Osamu Araki , Osamu Yokoi , Tatsumi Kusakabe , Yoshio Yamamoto , Susumu Ito , Tetsuro Nikuni
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