245 research outputs found
GÜVENİLİR HABERLEŞMEDE AÇIK KAPALI KAOTİK ANAHTARLAMA SİSTEMİNİN FPGA KULLANILARAK GERÇEKLEŞTİRİLMESİ
Bu çalışmada, kaotik tabanlı sayısal haberleşme örneği olan Açık Kapalı Kaotik Anahtarlama (AKKA) (Chaotic On Off Keying-COOK) haberleşme sisteminin bilgisayar benzetimeleri ve Alanda Programlanabilir Kapı Dizileri( Field Programming Gate Array-FPGA) kullanılarak uygulaması gerçekleştirilmiştir. Ayrıca çalışmada Hücresel Sinir Ağı (HSA) (Cellular Neural Network –CNN) tabanlı bir kaos üreteci ve Sprott kaos üreteci kullanılarak COOK haberlerleşme sisteminin bit-hata oranı (bit error rate - BER) ve gürültü sinyal oranı (signal to noise ratio - SNR) karşılaştırmalı olarak ortaya konmuştur
Model-free inference of direct network interactions from nonlinear collective dynamics
The topology of interactions in network dynamical systems fundamentally
underlies their function. Accelerating technological progress creates massively
available data about collective nonlinear dynamics in physical, biological, and
technological systems. Detecting direct interaction patterns from those
dynamics still constitutes a major open problem. In particular, current
nonlinear dynamics approaches mostly require to know a priori a model of the
(often high dimensional) system dynamics. Here we develop a model-independent
framework for inferring direct interactions solely from recording the nonlinear
collective dynamics generated. Introducing an explicit dependency matrix in
combination with a block-orthogonal regression algorithm, the approach works
reliably across many dynamical regimes, including transient dynamics toward
steady states, periodic and non-periodic dynamics, and chaos. Together with its
capabilities to reveal network (two point) as well as hypernetwork (e.g., three
point) interactions, this framework may thus open up nonlinear dynamics options
of inferring direct interaction patterns across systems where no model is
known.Comment: 10 pages, 7 figure
A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning
Reservoir computing (RC), first applied to temporal signal processing, is a
recurrent neural network in which neurons are randomly connected. Once
initialized, the connection strengths remain unchanged. Such a simple structure
turns RC into a non-linear dynamical system that maps low-dimensional inputs
into a high-dimensional space. The model's rich dynamics, linear separability,
and memory capacity then enable a simple linear readout to generate adequate
responses for various applications. RC spans areas far beyond machine learning,
since it has been shown that the complex dynamics can be realized in various
physical hardware implementations and biological devices. This yields greater
flexibility and shorter computation time. Moreover, the neuronal responses
triggered by the model's dynamics shed light on understanding brain mechanisms
that also exploit similar dynamical processes. While the literature on RC is
vast and fragmented, here we conduct a unified review of RC's recent
developments from machine learning to physics, biology, and neuroscience. We
first review the early RC models, and then survey the state-of-the-art models
and their applications. We further introduce studies on modeling the brain's
mechanisms by RC. Finally, we offer new perspectives on RC development,
including reservoir design, coding frameworks unification, physical RC
implementations, and interaction between RC, cognitive neuroscience and
evolution.Comment: 51 pages, 19 figures, IEEE Acces
18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings
Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I
Table of Contents ........................ Page III
Symposium Committees .............. Page IV
Special Thanks ............................. Page V
Conference program (incl. page numbers of papers)
................... Page VI
Conference papers
Invited talks ................................ Page 1
Regular Papers ........................... Page 14
Wednesday, May 26th, 2010 ......... Page 15
Thursday, May 27th, 2010 .......... Page 110
Friday, May 28th, 2010 ............... Page 210
Author index ............................... Page XII
Cryptography and Its Applications in Information Security
Nowadays, mankind is living in a cyber world. Modern technologies involve fast communication links between potentially billions of devices through complex networks (satellite, mobile phone, Internet, Internet of Things (IoT), etc.). The main concern posed by these entangled complex networks is their protection against passive and active attacks that could compromise public security (sabotage, espionage, cyber-terrorism) and privacy. This Special Issue “Cryptography and Its Applications in Information Security” addresses the range of problems related to the security of information in networks and multimedia communications and to bring together researchers, practitioners, and industrials interested by such questions. It consists of eight peer-reviewed papers, however easily understandable, that cover a range of subjects and applications related security of information
MOCAST 2021
The 10th International Conference on Modern Circuit and System Technologies on Electronics and Communications (MOCAST 2021) will take place in Thessaloniki, Greece, from July 5th to July 7th, 2021. The MOCAST technical program includes all aspects of circuit and system technologies, from modeling to design, verification, implementation, and application. This Special Issue presents extended versions of top-ranking papers in the conference. The topics of MOCAST include:Analog/RF and mixed signal circuits;Digital circuits and systems design;Nonlinear circuits and systems;Device and circuit modeling;High-performance embedded systems;Systems and applications;Sensors and systems;Machine learning and AI applications;Communication; Network systems;Power management;Imagers, MEMS, medical, and displays;Radiation front ends (nuclear and space application);Education in circuits, systems, and communications
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