divya sharma hash based data text fusion using speech signal algorithm

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Ville Pulkki Communication Acoustics. An Introduction to Speech, Audio and Psychoacoustics

In communication acoustics, the communication channel consists of a sound source, a channel (acoustic and/or electric) and finally the receiver: the human auditory system, a complex and intricate system that shapes the way sound is heard. Thus, when developing techniques in communication acoustics, such as in speech, audio and aided hearing, it is important to understand the time–frequency–space resolution of hearing. This book facilitates the reader’s understanding and development of speech and audio techniques based on our knowledge of the auditory perceptual mechanisms by introducing the physical, signal-processing and psychophysical background to communication acoustics. It then provides a detailed explanation of sound technologies where a human listener is involved, including audio and speech techniques, sound quality measurement, hearing aids and audiology. Key features: Explains perceptually-based audio: the authors take a detailed but accessible engineering perspective on sound and hearing with a focus on the human place in the audio communications signal chain, from psychoacoustics and audiology to optimizing digital signal processing for human listening. Presents a wide overview of speech, from the human production of speech sounds and basics of phonetics to major speech technologies, recognition and synthesis of speech and methods for speech quality evaluation. Includes MATLAB examples that serve as an excellent basis for the reader’s own investigations into communication acoustics interaction schemes which intuitively combine touch, vision and voice for lifelike interactions.

8247.97 рублей

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Johannes Stahl Single Channel Phase-Aware Signal Processing in Speech Communication. Theory and Practice

An overview on the challenging new topic of phase-aware signal processing Speech communication technology is a key factor in human-machine interaction, digital hearing aids, mobile telephony, and automatic speech/speaker recognition. With the proliferation of these applications, there is a growing requirement for advanced methodologies that can push the limits of the conventional solutions relying on processing the signal magnitude spectrum. Single-Channel Phase-Aware Signal Processing in Speech Communication provides a comprehensive guide to phase signal processing and reviews the history of phase importance in the literature, basic problems in phase processing, fundamentals of phase estimation together with several applications to demonstrate the usefulness of phase processing. Key features: Analysis of recent advances demonstrating the positive impact of phase-based processing in pushing the limits of conventional methods. Offers unique coverage of the historical context, fundamentals of phase processing and provides several examples in speech communication. Provides a detailed review of many references and discusses the existing signal processing techniques required to deal with phase information in different applications involved with speech. The book supplies various examples and MATLAB® implementations delivered within the PhaseLab toolbox. Single-Channel Phase-Aware Signal Processing in Speech Communication is a valuable single-source for students, non-expert DSP engineers, academics and graduate students.

7734.34 рублей

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Vincent Savaux MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems

This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is presented, as well as some basics concerning the channel statistics and the transmission of an OFDM signal over a multipath channel. In Chapter 2, the proposed iterative algorithm for the noise variance and the channel estimation is detailed, and in Chapter 3, an application of the algorithm for the free-band detection is proposed. In both Chapters 2 and 3, the principle of the algorithm is presented in a simple way, and more elaborate developments are also provided. The different assumptions and assertions in the developments and the performance of the proposed method are validated through simulations, and compared to methods of the scientific literature

5473.51 рублей

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Michael Bowles Machine Learning in Python. Essential Techniques for Predictive Analysis

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

3749.08 рублей

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I. Gusti Ngurah Agung Panel Data Analysis using EViews

A comprehensive and accessible guide to panel data analysis using EViews software This book explores the use of EViews software in creating panel data analysis using appropriate empirical models and real datasets. Guidance is given on developing alternative descriptive statistical summaries for evaluation and providing policy analysis based on pool panel data. Various alternative models based on panel data are explored, including univariate general linear models, fixed effect models and causal models, and guidance on the advantages and disadvantages of each one is given. Panel Data Analysis using EViews: Provides step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empirical models and real datasets. Examines a variety of panel data models along with the author’s own empirical findings, demonstrating the advantages and limitations of each model. Presents growth models, time-related effects models, and polynomial models, in addition to the models which are commonly applied for panel data. Includes more than 250 examples divided into three groups of models (stacked, unstacked, and structured panel data), together with notes and comments. Provides guidance on which models not to use in a given scenario, along with advice on viable alternatives. Explores recent new developments in panel data analysis An essential tool for advanced undergraduate or graduate students and applied researchers in finance, econometrics and population studies. Statisticians and data analysts involved with data collected over long time periods will also find this book a useful resource.

11111.64 рублей

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Roger Woods FPGA-based Implementation of Signal Processing Systems

An important working resource for engineers and researchers involved in the design, development, and implementation of signal processing systems The last decade has seen a rapid expansion of the use of field programmable gate arrays (FPGAs) for a wide range of applications beyond traditional digital signal processing (DSP) systems. Written by a team of experts working at the leading edge of FPGA research and development, this second edition of FPGA-based Implementation of Signal Processing Systems has been extensively updated and revised to reflect the latest iterations of FPGA theory, applications, and technology. Written from a system-level perspective, it features expert discussions of contemporary methods and tools used in the design, optimization and implementation of DSP systems using programmable FPGA hardware. And it provides a wealth of practical insights—along with illustrative case studies and timely real-world examples—of critical concern to engineers working in the design and development of DSP systems for radio, telecommunications, audio-visual, and security applications, as well as bioinformatics, Big Data applications, and more. Inside you will find up-to-date coverage of: FPGA solutions for Big Data Applications, especially as they apply to huge data sets The use of ARM processors in FPGAs and the transfer of FPGAs towards heterogeneous computing platforms The evolution of High Level Synthesis tools—including new sections on Xilinx's HLS Vivado tool flow and Altera's OpenCL approach Developments in Graphical Processing Units (GPUs), which are rapidly replacing more traditional DSP systems FPGA-based Implementation of Signal Processing Systems, 2nd Edition is an indispensable guide for engineers and researchers involved in the design and development of both traditional and cutting-edge data and signal processing systems. Senior-level electrical and computer engineering graduates studying signal processing or digital signal processing also will find this volume of great interest.

8997.79 рублей

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Donald Reay S. Digital Signal Processing Using the ARM Cortex M4

Features inexpensive ARM® Cortex®-M4 microcontroller development systems available from Texas Instruments and STMicroelectronics. This book presents a hands-on approach to teaching Digital Signal Processing (DSP) with real-time examples using the ARM® Cortex®-M4 32-bit microprocessor. Real-time examples using analog input and output signals are provided, giving visible (using an oscilloscope) and audible (using a speaker or headphones) results. Signal generators and/or audio sources, e.g. iPods, can be used to provide experimental input signals. The text also covers the fundamental concepts of digital signal processing such as analog-to-digital and digital-to-analog conversion, FIR and IIR filtering, Fourier transforms, and adaptive filtering. Digital Signal Processing Using the ARM® Cortex®-M4: Uses a large number of simple example programs illustrating DSP concepts in real-time, in an electrical engineering laboratory setting Includes examples for both STM32F407 Discovery and the TM4C123 Launchpad, using Keil MDK-ARM, on a companion website Example programs for the TM4C123 Launchpad using Code Composer Studio version 6 available on companion website Digital Signal Processing Using the ARM® Cortex®-M4 serves as a teaching aid for university professors wishing to teach DSP using laboratory experiments, and for students or engineers wishing to study DSP using the inexpensive ARM® Cortex®-M4. Donald Reay is a lecturer in electrical engineering at Heriot-Watt University in Edinburgh, Scotland. He has also taught hands-on DSP, on a number of occasions, as a visiting lecturer at Zhejiang University in Hangzhou, China. He co-authored Digital Signal Processing and Applications with the TMS320C6713 and TMS320C6416 DSK, Second Edition (Wiley 2008) with Rulph Chassaing, and is the author of Digital Signal Processing and Applications with the OMAP-L138 eXperimenter (Wiley 2012).

6744.78 рублей

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Giudici Paolo Applied Data Mining for Business and Industry

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

14176.92 рублей

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Fayez Gebali Algorithms and Parallel Computing

There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. Programming a parallel computer requires closely studying the target algorithm or application, more so than in the traditional sequential programming we have all learned. The programmer must be aware of the communication and data dependencies of the algorithm or application. This book provides the techniques to explore the possible ways to program a parallel computer for a given application.

9349.1 рублей

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Yogesh Sharma C. A Guide to the Economic Removal of Metals from Aqueous Solutions

Water pollution is topic of immense and common concern throughout the world. This book presents the results and data from research and adsorption experiments carried out on the removal of nickel and chromium (as well as other metals) from aqueous solutions using modified silica sand.

6893.05 рублей

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Richard Middlestead W. Digital Communications with Emphasis on Data Modems. Theory, Analysis, Design, Simulation, Testing, and Applications

This book uses a practical approach in the application of theoretical concepts to digital communications in the design of software defined radio modems. This book discusses the design, implementation and performance verification of waveforms and algorithms appropriate for digital data modulation and demodulation in modern communication systems. Using a building-block approach, the author provides an introductory to the advanced understanding of acquisition and data detection using source and executable simulation code to validate the communication system performance with respect to theory and design specifications. The author focuses on theoretical analysis, algorithm design, firmware and software designs and subsystem and system testing. This book treats system designs with a variety of channel characteristics from very low to optical frequencies. This book offers system analysis and subsystem implementation options for acquisition and data detection appropriate to the channel conditions and system specifications, and provides test methods for demonstrating system performance. This book also: Outlines fundamental system requirements and related analysis that must be established prior to a detailed subsystem design Includes many examples that highlight various analytical solutions and case studies that characterize various system performance measures Discusses various aspects of atmospheric propagation using the spherical 4/3 effective earth radius model Examines Ionospheric propagation and uses the Rayleigh fading channel to evaluate link performance using several robust waveform modulations Contains end-of-chapter problems, allowing the reader to further engage with the text Digital Communications with Emphasis on Data Modems is a great resource for communication-system and digital signal processing engineers and students looking for in-depth theory as well as practical implementations.

14247.21 рублей

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Keshet Joseph Automatic Speech and Speaker Recognition. Large Margin and Kernel Methods

This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.

11494.8 рублей

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Hannu Oja Robust Correlation. Theory and Applications

This bookpresents material on both the analysis of the classical concepts of correlation and on the development of their robust versions, as well as discussing the related concepts of correlation matrices, partial correlation, canonical correlation, rank correlations, with the corresponding robust and non-robust estimation procedures. Every chapter contains a set of examples with simulated and real-life data. Key features: Makes modern and robust correlation methods readily available and understandable to practitioners, specialists, and consultants working in various fields. Focuses on implementation of methodology and application of robust correlation with R. Introduces the main approaches in robust statistics, such as Huber’s minimax approach and Hampel’s approach based on influence functions. Explores various robust estimates of the correlation coefficient including the minimax variance and bias estimates as well as the most B- and V-robust estimates. Contains applications of robust correlation methods to exploratory data analysis, multivariate statistics, statistics of time series, and to real-life data. Includes an accompanying website featuring computer code and datasets Features exercises and examples throughout the text using both small and large data sets. Theoretical and applied statisticians, specialists in multivariate statistics, robust statistics, robust time series analysis, data analysis and signal processing will benefit from this book. Practitioners who use correlation based methods in their work as well as postgraduate students in statistics will also find this book useful.

6658.7 рублей

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Saeed Vaseghi V. Advanced Digital Signal Processing and Noise Reduction

Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates and extends the chapters in the previous edition and includes two new chapters on MIMO systems, Correlation and Eigen analysis and independent component analysis. The wide range of topics covered in this book include Wiener filters, echo cancellation, channel equalisation, spectral estimation, detection and removal of impulsive and transient noise, interpolation of missing data segments, speech enhancement and noise/interference in mobile communication environments. This book provides a coherent and structured presentation of the theory and applications of statistical signal processing and noise reduction methods. Two new chapters on MIMO systems, correlation and Eigen analysis and independent component analysis Comprehensive coverage of advanced digital signal processing and noise reduction methods for communication and information processing systems Examples and applications in signal and information extraction from noisy data Comprehensive but accessible coverage of signal processing theory including probability models, Bayesian inference, hidden Markov models, adaptive filters and Linear prediction models Advanced Digital Signal Processing and Noise Reduction is an invaluable text for postgraduates, senior undergraduates and researchers in the fields of digital signal processing, telecommunications and statistical data analysis. It will also be of interest to professional engineers in telecommunications and audio and signal processing industries and network planners and implementers in mobile and wireless communication communities.

12261.12 рублей

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Сетевой экран ZYXEL USG110 [usg110-ru0102f]

Благодаря поддержке более совершенного шифрования Secure Hash Algorithm 2 (SHA-2) межсетевой экран VPN Firewall обеспечивает лучшую в своем классе защиту соединений VPN для обеспечения максимальной безопасности каналов связи бизнеса.

68399 рублей

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Christopher Price Microsoft Big Data Solutions

Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

3192.36 рублей

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Domingos P. The Master Algorithm

A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

1205 рублей

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Kristiina Jokinen Constructive Dialogue Modelling. Speech Interaction and Rational Agents

Dialogue management technology has developed rapidly over the years resulting in real-time applications like telephony directories, timetable enquiries, and in-car applications. However, the current technology is still largely based on models that use rigid command language type interactions, and the users need to adapt their human communication strategies to the needs of the technology. As an increasing number of interactive ubiquitous applications will appear, challenges for interaction technology concern especially natural, more human-friendly communication. Recent research has focused on developing speech-based interactive systems that aim to increase the system’s communicative competence. By including aspects of interaction beyond simple speech recognition and question-answer based interaction, applications with more conversational interfaces have become possible. New dialogue management technology needs to address the challenges in human-technology interaction, so that smart environments should not only enable user-controlled command interfaces but equip applications with a capability that affords easy and friendly interactions with the user. Dialogue Modelling: Speech Interaction and Rational Agents provides an overview of the current dialogue technology and research trends in spoken dialogue systems, presenting a coherent perspective of AI-based cooperative interaction management. The book complements existing research regarding human-computer interfaces, speech and language technology, and communication studies in general, bringing different view-points together and integrating them into a single point of reference. Constructive Dialogue Modelling: Presents a guide to spoken dialogue technology and current research trends. Provides an overview of human factors in dialogue systems and delivers a new metaphor for human-computer interaction and computer as agent. Explains the architecture of dialogue systems using examples from systems such as Interact and DUMAS Offers a comprehensive overview of original research into the new trends in speech dialogue technology in light of innovations such as ubiquitous computing. This book will provide essential reading for industrial designers and interface engineers, university researchers and teachers, computer scientists, human communication researchers, speech and language technologists, cognitive engineers/cognitive scientists, as well as social and media researchers, and psychologists. Advanced students and researchers in computer science, speech and language technologies, psychology and communication research will find this text of interest.

9808.9 рублей

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Dialogue management technology has developed rapidly over the years resulting in real-time applications like telephony directories, timetable enquiries, and in-car applications. However, the current technology is still largely based on models that use rigid command language type interactions, and the users need to adapt their human communication strategies to the needs of the technology. As an increasing number of interactive ubiquitous applications will appear, challenges for interaction technology concern especially natural, more human-friendly communication. Recent research has focused on developing speech-based interactive systems that aim to increase the system’s communicative competence. By including aspects of interaction beyond simple speech recognition and question-answer based interaction, applications with more conversational interfaces have become possible. New dialogue management technology needs to address the challenges in human-technology interaction, so that smart environments should not only enable user-controlled command interfaces but equip applications with a capability that affords easy and friendly interactions with the user. Dialogue Modelling: Speech Interaction and Rational Agents provides an overview of the current dialogue technology and research trends in spoken dialogue systems, presenting a coherent perspective of AI-based cooperative interaction management. The book complements existing research regarding human-computer interfaces, speech and language technology, and communication studies in general, bringing different view-points together and integrating them into a single point of reference. Constructive Dialogue Modelling: Presents a guide to spoken dialogue technology and current research trends. Provides an overview of human factors in dialogue systems and delivers a new metaphor for human-computer interaction and computer as agent. Explains the architecture of dialogue systems using examples from systems such as Interact and DUMAS Offers a comprehensive overview of original research into the new trends in speech dialogue technology in light of innovations such as ubiquitous computing. This book will provide essential reading for industrial designers and interface engineers, university researchers and teachers, computer scientists, human communication researchers, speech and language technologists, cognitive engineers/cognitive scientists, as well as social and media researchers, and psychologists. Advanced students and researchers in computer science, speech and language technologies, psychology and communication research will find this text of interest.

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