Machine Learning Algorithms For Signal And Image Processing

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Machine Learning Algorithms for Signal and Image Processing

Author : Deepika Ghai
Publisher : John Wiley & Sons
ISBN 13 : 1119861845
Total Pages : 516 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Machine Learning Algorithms for Signal and Image Processing by : Deepika Ghai

Download or read book Machine Learning Algorithms for Signal and Image Processing written by Deepika Ghai and published by John Wiley & Sons. This book was released on 2022-11-18 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Machine Learning for Signal Processing

Author : Max A. Little
Publisher : Oxford University Press, USA
ISBN 13 : 0198714939
Total Pages : 378 pages
Book Rating : 4.1/5 (987 download)

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Book Synopsis Machine Learning for Signal Processing by : Max A. Little

Download or read book Machine Learning for Signal Processing written by Max A. Little and published by Oxford University Press, USA. This book was released on 2019 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Signal Processing and Machine Learning with Applications

Author : Michael M. Richter
Publisher : Springer
ISBN 13 : 9783319453712
Total Pages : 0 pages
Book Rating : 4.4/5 (537 download)

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Book Synopsis Signal Processing and Machine Learning with Applications by : Michael M. Richter

Download or read book Signal Processing and Machine Learning with Applications written by Michael M. Richter and published by Springer. This book was released on 2022-10-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Author : Nilanjan Dey
Publisher : Academic Press
ISBN 13 : 012816087X
Total Pages : 348 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by : Nilanjan Dey

Download or read book Machine Learning in Bio-Signal Analysis and Diagnostic Imaging written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Biomedical Signal and Image Processing with Artificial Intelligence

Author : Chirag Paunwala
Publisher : Springer Nature
ISBN 13 : 3031158164
Total Pages : 423 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Biomedical Signal and Image Processing with Artificial Intelligence by : Chirag Paunwala

Download or read book Biomedical Signal and Image Processing with Artificial Intelligence written by Chirag Paunwala and published by Springer Nature. This book was released on 2023-01-09 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on advanced techniques used for feature extraction, analysis, recognition, and classification in the area of biomedical signal and image processing. Contributions cover all aspects of artificial intelligence, machine learning, and deep learning in the field of biomedical signal and image processing using novel and unexplored techniques and methodologies. The book covers recent developments in both medical images and signals analyzed by artificial intelligence techniques. The authors also cover topics related to development based artificial intelligence, which includes machine learning, neural networks, and deep learning. This book will provide a platform for researchers who are working in the area of artificial intelligence for biomedical applications. Provides insights into medical signal and image analysis using artificial intelligence; Includes novel and recent trends of decision support system for medical research; Outlines employment of evolutionary algorithms for biomedical data, big data analysis for medical databases, and reliability, opportunities, and challenges in clinical data.

Machine Learning in Signal Processing

Author : Sudeep Tanwar
Publisher : CRC Press
ISBN 13 : 1000487814
Total Pages : 488 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Machine Learning in Signal Processing by : Sudeep Tanwar

Download or read book Machine Learning in Signal Processing written by Sudeep Tanwar and published by CRC Press. This book was released on 2021-12-10 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim to solve some of the biggest challenges in AI and ML. FEATURES Focuses on addressing the missing connection between signal processing and ML Provides a one-stop guide reference for readers Oriented toward material and flow with regards to general introduction and technical aspects Comprehensively elaborates on the material with examples and diagrams This book is a complete resource designed exclusively for advanced undergraduate students, post-graduate students, research scholars, faculties, and academicians of computer science and engineering, computer science and applications, and electronics and telecommunication engineering.

Learning Approaches in Signal Processing

Author : Wan-Chi Siu
Publisher : CRC Press
ISBN 13 : 0429592264
Total Pages : 678 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Learning Approaches in Signal Processing by : Wan-Chi Siu

Download or read book Learning Approaches in Signal Processing written by Wan-Chi Siu and published by CRC Press. This book was released on 2018-12-07 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an up-to-date tutorial and overview on learning technologies such as random forests, sparsity, and low-rank matrix estimation and cutting-edge visual/signal processing techniques, including face recognition, Kalman filtering, and multirate DSP. It discusses the applications that make use of deep learning, convolutional neural networks, random forests, etc.

Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision

Author : Karm Veer Arya
Publisher :
ISBN 13 : 9781774914687
Total Pages : 0 pages
Book Rating : 4.9/5 (146 download)

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Book Synopsis Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision by : Karm Veer Arya

Download or read book Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision written by Karm Veer Arya and published by . This book was released on 2024 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Artificial Intelligence and Machine Learning Techniques in Image Processing and Computer Vision provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. It is a roadmap for the improvement of computer vision and image processing, explaining the machine learning algorithms and models involved. The authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides real-world examples to illustrate the concepts and methods. The authors discuss machine learning in healthcare systems for detection, diagnosis, classification, and segmentation. They also explore the diverse applications of image and video processing, including image colorization and restoration using deep learning, using machine learning to record the changes in the Amazon rainforest over time with remote sensing, and more. Researchers, teachers, and students working in the field of artificial intelligence, machine learning, and computer vision will benefit from the knowledge presented here on the diverse applications of computer vision and image processing"--

Machine Learning for Audio, Image and Video Analysis

Author : Francesco Camastra
Publisher : Springer
ISBN 13 : 144716735X
Total Pages : 564 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Machine Learning for Audio, Image and Video Analysis by : Francesco Camastra

Download or read book Machine Learning for Audio, Image and Video Analysis written by Francesco Camastra and published by Springer. This book was released on 2015-07-21 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with self-contained introductions to the mathematical background necessary to read the book. Divided into three main parts, From Perception to Computation introduces methodologies aimed at representing the data in forms suitable for computer processing, especially when it comes to audio and images. Whilst the second part, Machine Learning includes an extensive overview of statistical techniques aimed at addressing three main problems, namely classification (automatically assigning a data sample to one of the classes belonging to a predefined set), clustering (automatically grouping data samples according to the similarity of their properties) and sequence analysis (automatically mapping a sequence of observations into a sequence of human-understandable symbols). The third part Applications shows how the abstract problems defined in the second part underlie technologies capable to perform complex tasks such as the recognition of hand gestures or the transcription of handwritten data. Machine Learning for Audio, Image and Video Analysis is suitable for students to acquire a solid background in machine learning as well as for practitioners to deepen their knowledge of the state-of-the-art. All application chapters are based on publicly available data and free software packages, thus allowing readers to replicate the experiments.

Deep Learning for Multimedia Processing Applications

Author : Uzair Aslam Bhatti
Publisher : CRC Press
ISBN 13 : 1003828051
Total Pages : 481 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Deep Learning for Multimedia Processing Applications by : Uzair Aslam Bhatti

Download or read book Deep Learning for Multimedia Processing Applications written by Uzair Aslam Bhatti and published by CRC Press. This book was released on 2024-02-21 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing. Divided into two volumes, Volume Two delves into advanced topics such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs), explaining their unique capabilities in multimedia tasks. Readers will discover how deep learning techniques enable accurate and efficient image recognition, object detection, semantic segmentation, and image synthesis. The book also covers video analysis techniques, including action recognition, video captioning, and video generation, highlighting the role of deep learning in extracting meaningful information from videos. Furthermore, the book explores audio processing tasks such as speech recognition, music classification, and sound event detection using deep learning models. It demonstrates how deep learning algorithms can effectively process audio data, opening up new possibilities in multimedia applications. Lastly, the book explores the integration of deep learning with natural language processing techniques, enabling systems to understand, generate, and interpret textual information in multimedia contexts. Throughout the book, practical examples, code snippets, and real-world case studies are provided to help readers gain hands-on experience in implementing deep learning solutions for multimedia processing. Deep Learning for Multimedia Processing Applications is an essential resource for anyone interested in harnessing the power of deep learning to unlock the vast potential of multimedia data.

Hyperspectral Image Analysis

Author : Saurabh Prasad
Publisher : Springer Nature
ISBN 13 : 3030386171
Total Pages : 464 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Hyperspectral Image Analysis by : Saurabh Prasad

Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.

Signal Processing and Machine Learning for Brain-Machine Interfaces

Author : Toshihisa Tanaka
Publisher : Institution of Engineering and Technology
ISBN 13 : 1785613987
Total Pages : 355 pages
Book Rating : 4.7/5 (856 download)

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Book Synopsis Signal Processing and Machine Learning for Brain-Machine Interfaces by : Toshihisa Tanaka

Download or read book Signal Processing and Machine Learning for Brain-Machine Interfaces written by Toshihisa Tanaka and published by Institution of Engineering and Technology. This book was released on 2018-09-13 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Brain-machine interfacing or brain-computer interfacing (BMI/BCI) is an emerging and challenging technology used in engineering and neuroscience. The ultimate goal is to provide a pathway from the brain to the external world via mapping, assisting, augmenting or repairing human cognitive or sensory-motor functions.

Advanced Machine Intelligence and Signal Processing

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 9811908400
Total Pages : 859 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Advanced Machine Intelligence and Signal Processing by : Deepak Gupta

Download or read book Advanced Machine Intelligence and Signal Processing written by Deepak Gupta and published by Springer Nature. This book was released on 2022-06-25 with total page 859 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing, and their applications in real world. The topics covered in machine learning involve feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modeling from video, 3D object recognition, localization and tracking, medical image analysis, and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multitask, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG), and electromyogram (EMG).

Adaptive Blind Signal and Image Processing

Author : Andrzej Cichocki
Publisher : John Wiley & Sons
ISBN 13 : 9780471607915
Total Pages : 596 pages
Book Rating : 4.6/5 (79 download)

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Book Synopsis Adaptive Blind Signal and Image Processing by : Andrzej Cichocki

Download or read book Adaptive Blind Signal and Image Processing written by Andrzej Cichocki and published by John Wiley & Sons. This book was released on 2002-06-14 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Im Mittelpunkt dieses modernen und spezialisierten Bandes stehen adaptive Strukturen und unüberwachte Lernalgorithmen, besonders im Hinblick auf effektive Computersimulationsprogramme. Anschauliche Illustrationen und viele Beispiele sowie eine interaktive CD-ROM ergänzen den Text.

Neural Networks, Machine Learning, and Image Processing

Author : Manoj Sahni
Publisher : CRC Press
ISBN 13 : 1000814297
Total Pages : 221 pages
Book Rating : 4.0/5 (8 download)

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Book Synopsis Neural Networks, Machine Learning, and Image Processing by : Manoj Sahni

Download or read book Neural Networks, Machine Learning, and Image Processing written by Manoj Sahni and published by CRC Press. This book was released on 2022-12-15 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: SECTION I Mathematical Modeling and Neural Network’ Mathematical Essence Chapter 1 Mathematical Modeling on Thermoregulation in Sarcopenia 1.1. Introduction 1.2. Discretization 1.3. Modeling and Simulation of Basal Metabolic Rate and Skin Layers Thickness 1.4. Mathematical Model and Boundary Conditions 1.5. Solution of the Model 1.6. Numerical Results and discussion 1.7. Conclusion References Chapter 2 Multi-objective University Course Scheduling for Uncertainly Generated Courses 2.1 Introduction 2.2 Literature review 2.3 Formulation of problem 2.4 Methodology 2.5 Numerical Example 2.6 Result and Discussion 2.7 Conclusion References Chapter 3 MChCNN : A Deep Learning Approach to Detect Text based Hate Speech 3.1. Introduction Background and Driving Forces 3.2. Related Work 3.3. Experiment and Results 3.4. Conclusion References Chapter 4 PSO Based PFC Cuk Converter fed BLDC Motor Drive for Automotive Applications 4.1. Introduction 4.2. Operation of Cuk converter fed BLDC motor drive system 4.3. Controller Operation 4.4. Result and Discussion 4.5. Conclusion References Chapter 5 Optimize Feature Selection for Condition based monitoring of Cylindrical bearing using Wavelet transform and ANN 5.1. Introduction 5.2. Methodology 5.3. Data Preparation 5.4. Result and Discussion 5.5. Conclusion References Chapter 6 SafeShop - An integrated system for safe pickup of items during COVID-19 6.1. Introduction 6.2. Literature Survey 6.3. Methodology 6.4. Result and Discussion 6.5. Conclusion References Chapter 7 Solution of First Order Fuzzy Differential Equation using Numerical Method 7.1. Introduction 7.2. Preliminaries 7.3. Methodology 7.4. Illustration 7.5. Conclusion References SECTION II Simulations in Machine Learning and Image Processing Chapter 8 Multi-layer Encryption Algorithm for Data Integrity in Cloud Computing 8.1. Introduction 8.2. Related works 8.3. Algorithm description 8.4. Simulation and performance analysis 8.5. Conclusion and Future Work References Chapter 9 Anomaly detection using class of supervised and unsupervised learning algorithms 9. 1. Introduction 9.2. Adaptive threshold and regression techniques for anomaly detection 9.3. Unsupervised Learning techniques for anomaly detection 9.4. Description of the dataset 9.5 Results and Discussions 9.6. Conclusion References Chapter 10 Improving Support Vector Machine accuracy with Shogun’s multiple kernel learning 10. 1. Introduction 10. 2. Support Vector Machine Statistics 10.3. Experiment and Result 10.4 Conclusion References Chapter 11 An Introduction to Parallelisable String-Based SP-Languages 11.1. Introduction 11.2. Parallelisable string-based SP-languages 11.3. Parallel Regular Expression 11.4. Equivalence of Parallel Regular Expression and Branching Automaton 11.5. Parallelisable String-Based SP-Grammar 11.6. Parallelisable String-Based SP-Parallel Grammar 11.7. Conclusion 11.8. Applications 11.9. Future Scope References Chapter 12 Detection of Disease using Machine Learning 12.1. Introduction 12.2. Techniques Applied 12.3. GENERAL ARCHITECTURE OF AI/ML 12.4. EXPERIMENTAL OUTCOMES 12.5. Conclusion References Chapter 13 Driver Drowsiness Detection Using Eye Tracing System 13.1. Introduction 13.2. Literature Review 13.3. Research Method 13.4. Observations and Results 13.5. Conclusion References Chapter 14 An Efficient Image Encryption Scheme Combining Rubik Cube Principle with Masking 14.1 Introduction 14.2 Preliminary Section 14.3 Proposed Work 14. 4 Experimental Setup and Simulation Analysis 14.5 Conclusion References

Fast Algorithms for Signal Processing

Author : Richard E. Blahut
Publisher : Cambridge University Press
ISBN 13 : 1139487957
Total Pages : 469 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Fast Algorithms for Signal Processing by : Richard E. Blahut

Download or read book Fast Algorithms for Signal Processing written by Richard E. Blahut and published by Cambridge University Press. This book was released on 2010-06-24 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing and four-dimensional medical imaging. This self-contained guide, the only one of its kind, enables engineers to find the optimum fast algorithm for a specific application. It presents a broad range of computationally-efficient algorithms, describes their structure and implementation, and compares their relative strengths for given problems. All the necessary background mathematics is included and theorems are rigorously proved, so all the information needed to learn and apply the techniques is provided in one convenient guide. With this practical reference, researchers and practitioners in electrical engineering, applied mathematics, and computer science can reduce power dissipation for low-end applications of signal processing, and extend the reach of high-end applications.

Cognitive Systems and Signal Processing in Image Processing

Author : Yu-Dong Zhang
Publisher : Academic Press
ISBN 13 : 0323860095
Total Pages : 398 pages
Book Rating : 4.3/5 (238 download)

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Book Synopsis Cognitive Systems and Signal Processing in Image Processing by : Yu-Dong Zhang

Download or read book Cognitive Systems and Signal Processing in Image Processing written by Yu-Dong Zhang and published by Academic Press. This book was released on 2021-11-28 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time. Presents cognitive signal processing methodologies that are related to challenging image processing application domains Provides the state-of-the-art in cognitive signal processing approaches in the area of big-data image processing Focuses on other technical aspects and alternatives to traditional tools, algorithms and methodologies Discusses various real-time case studies and implemented works