1.

Record Nr.

UNISA996550550803316

Autore

Kumar Amit

Titolo

Proceedings of the 2nd International Conference on Cognitive and Intelligent Computing [[electronic resource] ] : ICCIC 2022, 27–28 December, Hyderabad, India; Volume 1 / / edited by Amit Kumar, Gheorghita Ghinea, Suresh Merugu

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023

ISBN

981-9927-42-0

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (755 pages)

Collana

Cognitive Science and Technology, , 2195-3996

Altri autori (Persone)

GhineaGheorghita

MeruguSuresh

Disciplina

006.3

Soggetti

Computational intelligence

Machine learning

Artificial intelligence

Data mining

Internet of things

Computational Intelligence

Machine Learning

Artificial Intelligence

Data Mining and Knowledge Discovery

Internet of Things

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Making Cell- Free Massive MIMO using MRC technique -- VIP Development of SPI Controller for Open-Power Processor Based Fabless SOC -- Cell-Free Massive MIMO versus Small Cells -- High Precision Navigation using Particle Swarm Optimization based KF -- Recent Advancements for Detection and Prediction of Breast Cancer using Deep Learning A Review.

Sommario/riassunto

This book includes original, peer-reviewed articles from the 2nd International Conference on Cognitive & Intelligent Computing (ICCIC-2022), held at Vasavi College of Engineering Hyderabad, India. It covers the latest trends and developments in areas of cognitive computing,



intelligent computing, machine learning, smart cities, IoT, artificial intelligence, cyber-physical systems, cybernetics, data science, neural network, and cognition. This book addresses the comprehensive nature of computational intelligence, cognitive computing, AI, ML, and DL to emphasize its character in modeling, identification, optimization, prediction, forecasting, and control of future intelligent systems. Submissions are original, unpublished, and present in-depth fundamental research contributions either from a methodological/application perspective in understanding artificial intelligence and machine learning approaches and their capabilities in solving diverse range of problems in industries and its real-world applications.

2.

Record Nr.

UNINA9910820990503321

Autore

Sonnenschein Bernard

Titolo

Collective dynamics in complex networks of noisy phase oscillators : towards models of neuronal network dynamics / / von M.Sc. Bernard Sonnenschein

Pubbl/distr/stampa

Berlin : , : Logos Verlag Berlin, , [2016]

©2016

ISBN

3-8325-8825-6

Descrizione fisica

1 online resource (vi, 118 pages)

Disciplina

531.32015118

Soggetti

Oscillations - Mathematical models

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

PublicationDate: 20161121

Nota di bibliografia

Includes bibliographical references.

Sommario/riassunto

Long description: This work aims to contribute to our understanding of the effects of noise and non-uniform interactions in populations of oscillatory units. In particular, we explore the collective dynamics in various extensions of the Kuramoto model. We develop a theoretical framework to study such noisy systems and we show through many examples that indeed new insights can be gained with our method. The first step is to coarse-grain the complex networks. The oscillatory units



are then characterized solely by their individual quantities, so that identical units can be grouped together. The second step consists of the ansatz that in all these groups the distributions of the oscillators' phases follow time-dependent Gaussians. We apply this analytical two-step method to oscillator networks with correlations between coupling strengths and natural frequencies, to populations with mixed positive and negative coupling strengths, and to noise-driven active rotators, which can perform excitable dynamics. We calculate the rich phase diagrams that delineate the emergent rhythms. Extensive numerical simulations are performed to show both the validity and the limitations of our theoretical results.