Optimization of Spiking Neural Networks for Radar Applications PDF Download
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Author: Muhammad Arsalan
Publisher: Springer Nature
ISBN: 3658453184
Category :
Languages : en
Pages : 253
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Book Description
Author: Muhammad Arsalan
Publisher: Springer Nature
ISBN: 3658453184
Category :
Languages : en
Pages : 253
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Book Description
Author: Ali Safa
Publisher: Springer Nature
ISBN: 3031635655
Category :
Languages : en
Pages : 224
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Book Description
Author: Haijun Zhang
Publisher: Springer Nature
ISBN: 9819770017
Category :
Languages : en
Pages : 489
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Book Description
Author: Gexiang Zhang
Publisher: Springer
ISBN: 3319559893
Category : Technology & Engineering
Languages : en
Pages : 365
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Book Description
This book thoroughly investigates the underlying theoretical basis of membrane computing models, and reveals their latest applications. In addition, to date there have been no illustrative case studies or complex real-life applications that capitalize on the full potential of the sophisticated membrane systems computational apparatus; gaps that this book remedies. By studying various complex applications – including engineering optimization, power systems fault diagnosis, mobile robot controller design, and complex biological systems involving data modeling and process interactions – the book also extends the capabilities of membrane systems models with features such as formal verification techniques, evolutionary approaches, and fuzzy reasoning methods. As such, the book offers a comprehensive and up-to-date guide for all researchers, PhDs and undergraduate students in the fields of computer science, engineering and the bio-sciences who are interested in the applications of natural computing models.
Author: Zhan Li
Publisher: Frontiers Media SA
ISBN: 2889744892
Category : Science
Languages : en
Pages : 182
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Book Description
Author: Kundan Meshram
Publisher: Elsevier
ISBN: 0443153639
Category : Technology & Engineering
Languages : en
Pages : 220
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Book Description
Machine Learning Applications in Civil Engineering discusses machine learning and deep learning models for different civil engineering applications. These models work for stochastic methods wherein internal processing is done using randomized prototypes. The book explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency. It introduces Machine Learning and its applications to different Civil Engineering tasks, including Basic Machine Learning Models for data pre-processing, models for data representation, classification models for Civil Engineering Applications, Bioinspired Computing models for Civil Engineering, and their case studies. Using this book, civil engineering students and researchers can deep dive into Machine Learning, and identify various solutions to practical Civil Engineering tasks. - Introduces various ML models for Civil Engineering Applications that will assist readers in their analysis of design and development interfaces for building these applications - Reviews different lacunas and challenges in current models used for Civil Engineering scenarios - Explores designs for customized components for optimum system deployment - Explains various machine learning model designs that will assist researchers to design multi domain systems with maximum efficiency
Author: Huchuan Lu
Publisher: Springer
ISBN: 3030228088
Category : Computers
Languages : en
Pages : 630
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Book Description
This two-volume set LNCS 11554 and 11555 constitutes the refereed proceedings of the 16th International Symposium on Neural Networks, ISNN 2019, held in Moscow, Russia, in July 2019. The 111 papers presented in the two volumes were carefully reviewed and selected from numerous submissions. The papers were organized in topical sections named: Learning System, Graph Model, and Adversarial Learning; Time Series Analysis, Dynamic Prediction, and Uncertain Estimation; Model Optimization, Bayesian Learning, and Clustering; Game Theory, Stability Analysis, and Control Method; Signal Processing, Industrial Application, and Data Generation; Image Recognition, Scene Understanding, and Video Analysis; Bio-signal, Biomedical Engineering, and Hardware.
Author: Mukesh Saraswat
Publisher: Springer Nature
ISBN: 9811691134
Category : Technology & Engineering
Languages : en
Pages : 914
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Book Description
This book is a collection of selected papers presented at the Second Congress on Intelligent Systems (CIS 2021), organized by Soft Computing Research Society and CHRIST (Deemed to be University), Bengaluru, India during September 4 – 5, 2021. It includes novel and innovative work from experts, practitioners, scientists and decision-makers from academia and industry. It covers topics such as Internet of Things, information security, embedded systems, real-time systems, cloud computing, big data analysis, quantum computing, automation systems, bio-inspired intelligence, cognitive systems, cyber physical systems, data analytics, data/web mining, data science, intelligence for security, intelligent decision making systems, intelligent information processing, intelligent transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video classification, soft computing for machine vision, pattern recognition, human computer interaction, robotic devices and systems, autonomous vehicles, intelligent control systems, human motor control, game playing, evolutionary algorithms, swarm optimization, neural network, deep learning, supervised learning, unsupervised learning, fuzzy logic, rough sets, computational optimization, and neuro fuzzy systems.
Author: Amit Kumar
Publisher: Springer Nature
ISBN: 9819780438
Category :
Languages : en
Pages : 1425
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Book Description
Author: Raquel Cruz Conceição
Publisher: Springer
ISBN: 3319278665
Category : Science
Languages : en
Pages : 154
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Book Description
This book collates past and current research on one of the most promising emerging modalities for breast cancer detection. Readers will discover how, as a standalone technology or in conjunction with another modality, microwave imaging has the potential to provide reliable, safe and comfortable breast exams at low cost. Current breast imaging modalities include X- ray, Ultrasound, Magnetic Resonance Imaging, and Positron Emission Tomography. Each of these methods suffers from limitations, including poor sensitivity or specificity, high cost, patient discomfort, and exposure to potentially harmful ionising radiation. Microwave breast imaging is based on a contrast in the dielectric properties of breast tissue that exists at microwave frequencies. The book begins by considering the anatomy and dielectric properties of the breast, contrasting historical and recent studies. Next, radar-based breast imaging algorithms are discussed, encompassing both early-stage artefact removal, and data independent and adaptive beamforming algorithms. In a similar fashion, microwave tomographic reconstruction algorithms are reviewed in the following chapter, introducing the reader to both the fundamental and more advanced algorithms. Apart from imaging, the book also reviews research efforts in extracting clinically useful information from the Radar Target Signature of breast tumours, which is used to classify tumours as either benign or malignant. Finally, the book concludes by describing the current state of the art in terms of prototype microwave breast imaging systems, with a particular emphasis on those which have progressed to the clinical evaluation stage. This work is motivated by the fact that breast cancer is one of the leading causes of death amongst women in Europe and the US, and the second most common cancer in the world today. Such an important area of research will appeal to many scholars and practitioners.p>
