Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Deep Neural Network Design For Radar Applications
Download Deep Neural Network Design For Radar Applications full books in PDF, epub, and Kindle. Read online Deep Neural Network Design For Radar Applications ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Deep Neural Network Design for Radar Applications by : Sevgi Zubeyde Gurbuz
Download or read book Deep Neural Network Design for Radar Applications written by Sevgi Zubeyde Gurbuz and published by SciTech Publishing. This book was released on 2020-12-31 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking to apply these technologies ought to be aware of.
Book Synopsis Deep Learning Applications of Short-Range Radars by : Avik Santra
Download or read book Deep Learning Applications of Short-Range Radars written by Avik Santra and published by Artech House. This book was released on 2020-09-30 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This exciting new resource covers various emerging applications of short range radars, including people counting and tracking, gesture sensing, human activity recognition, air-drawing, material classification, object classification, vital sensing by extracting features such as range-Doppler Images (RDI), range-cross range images, Doppler Spectrogram or directly feeding raw ADC data to the classifiers. The book also presents how deep learning architectures are replacing conventional radar signal processing pipelines enabling new applications and results. It describes how deep convolutional neural networks (DCNN), long-short term memory (LSTM), feedforward networks, regularization, optimization algorithms, connectionist This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book covers applications ranging from industrial, consumer space to emerging automotive applications. The book presents several human-machine interface (HMI) applications, such as gesture recognition and sensing, human activity classification, air-writing, material classification, vital sensing, people sensing, people counting, people localization and in-cabin automotive occupancy and smart trunk opening. The underpinnings of deep learning are explored, outlining the history of neural networks and the optimization algorithms to train them. Modern deep convolutional neural network (DCNN), popular DCNN architectures for computer vision and their features are also introduced. The book presents other deep learning architectures, such as long-short term memory (LSTM), auto-encoders, variational auto-encoders (VAE), and generative adversarial networks (GAN). The application of human activity recognition as well as the application of air-writing using a network of short-range radars are outlined. This book demonstrates and highlights how deep learning is enabling several advanced industrial, consumer and in-cabin applications of short-range radars, which weren't otherwise possible. It illustrates various advanced applications, their respective challenges, and how they are been addressed using different deep learning architectures and algorithms.
Book Synopsis Methods & Techniques in Deep Learning by : Avik Santra
Download or read book Methods & Techniques in Deep Learning written by Avik Santra and published by John Wiley & Sons. This book was released on 2022-12-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces multiple state-of-the-art deep learning architectures for mmwave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmwave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrate how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmwave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmwave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science and AI.
Book Synopsis Neural Network Design by : Martin T. Hagan
Download or read book Neural Network Design written by Martin T. Hagan and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Women in Telecommunications by : Maria Sabrina Greco
Download or read book Women in Telecommunications written by Maria Sabrina Greco and published by Springer Nature. This book was released on 2023-11-06 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a breadth of innovative and impactful research in the field of telecommunications led by women investigators. Topics covered include satellite communications, cognitive radars, remote sensing sensor networks, quantum Internet, and cyberspace. These topics touch on many of the challenges facing the world today and these solutions by women researchers are valuable for their technical excellence and their non-traditional perspective. As an important part of the Women in Engineering and Science book series, the work highlights the contribution of women leaders in telecommunications, inspiring women and men, girls and boys to enter and apply themselves to secure our future in.
Book Synopsis Millimeter Wave Radar by : Stephen L. Johnston
Download or read book Millimeter Wave Radar written by Stephen L. Johnston and published by . This book was released on 1980 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Bioinformatics and Biomedical Engineering by : Ignacio Rojas
Download or read book Bioinformatics and Biomedical Engineering written by Ignacio Rojas and published by Springer Nature. This book was released on 2023-06-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the proceedings of the 10th International Work-Conference on IWBBIO 2023, held in Meloneras, Gran Canaria, Spain, during July 12-14, 2022. The total of 79 papers presented in the proceedings, was carefully reviewed and selected from 209 submissions. The papers cove the latest ideas and realizations in the foundations, theory, models, and applications for interdisciplinary and multidisciplinary research encompassing disciplines of computer science, mathematics, statistics, biology, bioinformatics, and biomedicine.
Book Synopsis Deep Learning for Radar and Communications Automatic Target Recognition by : Uttam K. Majumder
Download or read book Deep Learning for Radar and Communications Automatic Target Recognition written by Uttam K. Majumder and published by Artech House. This book was released on 2020-07-31 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
Book Synopsis Complex-valued Neural Networks by : Akira Hirose
Download or read book Complex-valued Neural Networks written by Akira Hirose and published by World Scientific. This book was released on 2003 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum neural devices and systems, spatiotemporal analysis of physiological neural systems, and artificial neural information processing. In this first-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from various points of view to provide academic and industrial researchers with a comprehensive understanding of the fundamentals, features and prospects of the powerful complex-valued networks.
Book Synopsis Machine Learning Applications in Electromagnetics and Antenna Array Processing by : Manel Martínez-Ramón
Download or read book Machine Learning Applications in Electromagnetics and Antenna Array Processing written by Manel Martínez-Ramón and published by Artech House. This book was released on 2021-04-30 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This practical resource provides an overview of machine learning (ML) approaches as applied to electromagnetics and antenna array processing. Detailed coverage of the main trends in ML, including uniform and random array processing (beamforming and detection of angle of arrival), antenna optimization, wave propagation, remote sensing, radar, and other aspects of electromagnetic design are explored. An introduction to machine learning principles and the most common machine learning architectures and algorithms used today in electromagnetics and other applications is presented, including basic neural networks, gaussian processes, support vector machines, kernel methods, deep learning, convolutional neural networks, and generative adversarial networks. Applications in electromagnetics and antenna array processing that are solved using machine learning are discussed, including antennas, remote sensing, and target classification.
Book Synopsis Deep Learning Applications, Volume 2 by : M. Arif Wani
Download or read book Deep Learning Applications, Volume 2 written by M. Arif Wani and published by Springer. This book was released on 2020-12-14 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments, and highlights novel ways of using deep neural networks to solve real-world problems. Also offering insights into deep learning architectures and algorithms, it is an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers.
Book Synopsis Signal Design for Modern Radar Systems by : Mohammad Alaee-Kerahroodi
Download or read book Signal Design for Modern Radar Systems written by Mohammad Alaee-Kerahroodi and published by Artech House. This book was released on 2022-11-30 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives you a comprehensive overview of key optimization tools that can be used to design radar waveforms and adaptive signal processing strategies under practical constraints -- strategies such as power method-like iterations, coordinate descent, and majorization-minimization – that help you to meet the more and more stressing sensing system requirements. The book walks you through how radar waveform synthesis is obtained as the solution to a constrained optimization problem such as finite energy, unimodularity (or being constant-modulus), and finite or discrete-phase (potentially binary) alphabet, which are dictated by the practical limitations of the real systems. Several approaches in each of these broad frameworks are detailed and various applications of these optimization techniques are described. Focusing on a holistic approach rather than a problem-specific approach, the book shows you what you need to effectively formulate waveform design and understand the flexibility of the framework for adapting to your own specific needs. You’ll have full access to the tools and knowledge you need to design waveform with optimized correlation/cross-correlation properties for SISO/SIMO and MIMO radars, taking into account spectral constraints for cognitive rads, as well as coexistence with communications and mitigate possible Doppler and quantization errors, and more. The book also includes representative software codes that further help you generate the described solutions. With its unique style of covering mathematical results along with their applications from diverse areas, this is a much-needed, detailed handbook for industry researchers, scientists and designers including medical, marine, defense, and automotive companies. It is also an excellent resource for advanced courses on radar signal processing.
Book Synopsis Array and Wearable Antennas by : Puran Gour
Download or read book Array and Wearable Antennas written by Puran Gour and published by CRC Press. This book was released on 2024-03-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text highlights the designing of efficient, wearable, and textile antennas for medical and wireless applications. It further discusses antenna design for the Internet of Things, biomedical, and 5G applications. The book presents machine learning and deep learning techniques for antenna design and analysis. It also covers radio frequency, micro-electromechanical systems, and nanoelectromechanical systems devices for smart antenna design. This book: Explores wearable reconfigurable antennas for wireless communication and provide the latest technique in term of its structure, defective ground plane, and fractal design Focuses on current and future technologies related to antenna design, and channel characterization for different communication links, and applications Discusses machine learning techniques for antenna design and analysis Demonstrates how nano patch antenna resonates at multiple frequencies by varying the chemical potential Covers the latest antenna technology for microwave sensors, and for fiber optical sensor communications It is primarily for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering.
Book Synopsis Methods and Techniques in Deep Learning by : Avik Santra
Download or read book Methods and Techniques in Deep Learning written by Avik Santra and published by John Wiley & Sons. This book was released on 2022-11-21 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Methods and Techniques in Deep Learning Introduces multiple state-of-the-art deep learning architectures for mmWave radar in a variety of advanced applications Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and authoritative overview of the use of artificial intelligence (AI)-based processing for various mmWave radar applications. Focusing on practical deep learning techniques, this comprehensive volume explains the fundamentals of deep learning, reviews cutting-edge deep metric learning techniques, describes different typologies of reinforcement learning (RL) algorithms, highlights how domain adaptation (DA) can be used for improving the performance of machine learning (ML) algorithms, and more. Throughout the book, readers are exposed to product-ready deep learning solutions while learning skills that are relevant for building any industrial-grade, sensor-based deep learning solution. A team of authors with more than 70 filed patents and 100 published papers on AI and sensor processing illustrates how deep learning is enabling a range of advanced industrial, consumer, and automotive applications of mmWave radars. In-depth chapters cover topics including multi-modal deep learning approaches, the elemental blocks required to formulate Bayesian deep learning, how domain adaptation (DA) can be used for improving the performance of machine learning algorithms, and geometric deep learning are used for processing point clouds. In addition, the book: Discusses various advanced applications and how their respective challenges have been addressed using different deep learning architectures and algorithms Describes deep learning in the context of computer vision, natural language processing, sensor processing, and mmWave radar sensors Demonstrates how deep parametric learning reduces the number of trainable parameters and improves the data flow Presents several human-machine interface (HMI) applications such as gesture recognition, human activity classification, human localization and tracking, in-cabin automotive occupancy sensing Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions is an invaluable resource for industry professionals, researchers, and graduate students working in systems engineering, signal processing, sensors, data science, and AI.
Book Synopsis Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure by : M. Z. Naser
Download or read book Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure written by M. Z. Naser and published by Elsevier. This book was released on 2023-11-01 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past few years have demonstrated how civil infrastructure continues to experience an unprecedented scale of extreme loading conditions (i.e. hurricanes, wildfires and earthquakes). Despite recent advancements in various civil engineering disciplines, specific to the analysis, design and assessment of structures, it is unfortunate that it is common nowadays to witness large scale damage in buildings, bridges and other infrastructure. The analysis, design and assessment of infrastructure comprises of a multitude of dimensions spanning a highly complex paradigm across material sciences, structural engineering, construction and planning among others. While traditional methods fall short of adequately accounting for such complexity, fortunately, computational intelligence presents novel solutions that can effectively tackle growing demands of intense extreme events and modern designs of infrastructure – especially in this era where infrastructure is reaching new heights and serving larger populations with high social awareness and expectations. Computational Intelligence for Analysis, Design and Assessment of Civil Infrastructure highlights the growing trend of fostering the use of CI to realize contemporary, smart and safe infrastructure. This is an emerging area that has not fully matured yet and hence the book will draw considerable interest and attention. In a sense, the book presents results of innovative efforts supplemented with case studies from leading researchers that can be used as benchmarks to carryout future experiments and/or facilitate development of future experiments and advanced numerical models. The book is written with the intention to serve as a guide for a wide audience including senior postgraduate students, academic and industrial researchers, materials scientists and practicing engineers working in civil, structural and mechanical engineering. Focuses on civil engineering applications for extreme events Explains the fundamentals of AI/ML and how they can be applied in civil engineering Features case study examples, design codes, and problems and solutions that would work for extreme events
Book Synopsis Multivariate Statistical Machine Learning Methods for Genomic Prediction by : Osval Antonio Montesinos López
Download or read book Multivariate Statistical Machine Learning Methods for Genomic Prediction written by Osval Antonio Montesinos López and published by Springer Nature. This book was released on 2022-02-14 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is open access under a CC BY 4.0 license This open access book brings together the latest genome base prediction models currently being used by statisticians, breeders and data scientists. It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool. To do so, for each tool the book provides background theory, some elements of the R statistical software for its implementation, the conceptual underpinnings, and at least two illustrative examples with data from real-world genomic selection experiments. Lastly, worked-out examples help readers check their own comprehension.The book will greatly appeal to readers in plant (and animal) breeding, geneticists and statisticians, as it provides in a very accessible way the necessary theory, the appropriate R code, and illustrative examples for a complete understanding of each statistical learning tool. In addition, it weighs the advantages and disadvantages of each tool.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1668424096 Total Pages :1575 pages Book Rating :4.6/5 (684 download)
Book Synopsis Research Anthology on Artificial Neural Network Applications by : Management Association, Information Resources
Download or read book Research Anthology on Artificial Neural Network Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-07-16 with total page 1575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.
