Manash Chanda – författare

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.

Features:

Addresses differential equation-based approaches to solve varied engineering problems Discusses derivation and solution of major equations of engineering and applied science Reviews qualitative and quantitative (numerical) analysis and mathematical modelling Includes mathematical models of the discussed problems Discusses MATLAB® codes

Features: code and online materials related to the differential equations.

This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.

Features:

Addresses differential equation-based approaches to solve varied engineering problems Discusses derivation and solution of major equations of engineering and applied science Reviews qualitative and quantitative (numerical) analysis and mathematical modelling Includes mathematical models of the discussed problems Discusses MATLAB® codes

Features: code and online materials related to the differential equations.

This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.Features:Addresses differential equation-based approaches to solve varied engineering problemsDiscusses derivation and solution of major equations of engineering and applied scienceReviews qualitative and quantitative (numerical) analysis and mathematical modellingIncludes mathematical models of the discussed problemsDiscusses MATLAB® codesFeatures: code and online materials related to the differential equations.This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.Features:Addresses differential equation-based approaches to solve varied engineering problemsDiscusses derivation and solution of major equations of engineering and applied scienceReviews qualitative and quantitative (numerical) analysis and mathematical modellingIncludes mathematical models of the discussed problemsDiscusses MATLAB® codesFeatures: code and online materials related to the differential equations.This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

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 processingHealthcare monitoring, biomedical systems, and green energyHow various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing timeReal applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detectionProfessionals 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 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 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.

This book teaches basic and advanced concepts, new methodologies and recent developments in VLSI technology with a focus on low power design. It provides insight on how to use Tanner Spice, Cadence tools, Xilinx tools, VHDL programming and Synopsis to design simple and complex circuits using latest state-of-the art technologies. Emphasis is placed on fundamental transistor circuit-level design concepts.

This book teaches basic and advanced concepts, new methodologies and recent developments in VLSI technology with a focus on low power design. It provides insight on how to use Tanner Spice, Cadence tools, Xilinx tools, VHDL programming and Synopsis to design simple and complex circuits using latest state-of-the art technologies. Emphasis is placed on fundamental transistor circuit-level design concepts.