Новые поступления

Antonio Napolitano Generalizations of Cyclostationary Signal Processing. Spectral Analysis and Applications antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
The relative motion between the transmitter and the receiver modifies the nonstationarity properties of the transmitted signal. In particular, the almost-cyclostationarity property exhibited by almost all modulated signals adopted in communications, radar, sonar, and telemetry can be transformed into more general kinds of nonstationarity. A proper statistical characterization of the received signal allows for the design of signal processing algorithms for detection, estimation, and classification that significantly outperform algorithms based on classical descriptions of signals.Generalizations of Cyclostationary Signal Processing addresses these issues and includes the following key features: Presents the underlying theoretical framework, accompanied by details of their practical application, for the mathematical models of generalized almost-cyclostationary processes and spectrally correlated processes; two classes of signals finding growing importance in areas such as mobile communications, radar and sonar. Explains second- and higher-order characterization of nonstationary stochastic processes in time and frequency domains. Discusses continuous- and discrete-time estimators of statistical functions of generalized almost-cyclostationary processes and spectrally correlated processes. Provides analysis of mean-square consistency and asymptotic Normality of statistical function estimators. Offers extensive analysis of Doppler channels owing to the relative motion between transmitter and receiver and/or surrounding scatterers. Performs signal analysis using both the classical stochastic-process approach and the functional approach, where statistical functions are built starting from a single function of time.
11512.84 RUR
François Auger Signal Processing with Free Software. Practical Experiments antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
An ideal resource for students, industrial engineers, and researchers, Signal Processing with Free Software Practical Experiments presents practical experiments in signal processing using free software. The text introduces elementary signals through elementary waveform, signal storage files and elementary operations on signals and then presents the first tools to signal analysis such as temporal and frequency characteristics leading to Time-frequency analysis. Non-parametric spectral analysis is also discussed as well as signal processing through sampling, resampling, quantification, and analog and digital filtering. Table of Contents: 1. Generation of Elementary Signals. Generation of Elementary Waveform. – Elementary Operations on the Signals. – Format of Signal Storage Files. 2. First tools of Signal Analysis. Measurement of Temporal and Frequency Characteristics of a Signal. Time-Frequency Analysis of a Signal. 3. Non-parametric Spectral Analysis. 4. Signal Processing. Sampling. – Resampling. – Quantification. – “Analog” Filtering. Digital Filtering
4835.39 RUR
Saeed Vaseghi V. Advanced Digital Signal Processing and Noise Reduction antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
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.
12280.36 RUR
Francis Castanié Digital Spectral Analysis. Parametric, Non-Parametric and Advanced Methods antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature. The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators. Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids. Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.
12664.12 RUR
Zhengyou He Wavelet Analysis and Transient Signal Processing Applications for Power Systems antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
An original reference applying wavelet analysis to power systems engineering • Introduces a modern signal processing method called wavelet analysis, and more importantly, its applications to power system fault detection and protection • Concentrates on its application to the power system, offering great potential for fault detection and protection • Presents applications, examples, and case studies, together with the latest research findings • Provides a combination of the author’s tutorial notes from electrical engineering courses together with his own original research work, of interest to both industry and academia
9855.64 RUR
Maurice Charbit Digital Signal and Image Processing using MATLAB, Volume 3. Advances and Applications, The Stochastic Case antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
Volume 3 of the second edition of the fully revised and updated Digital Signal and Image Processing using MATLAB®, after first two volumes on the “Fundamentals” and “Advances and Applications: The Deterministic Case”, focuses on the stochastic case. It will be of particular benefit to readers who already possess a good knowledge of MATLAB®, a command of the fundamental elements of digital signal processing and who are familiar with both the fundamentals of continuous-spectrum spectral analysis and who have a certain mathematical knowledge concerning Hilbert spaces. This volume is focused on applications, but it also provides a good presentation of the principles. A number of elements closer in nature to statistics than to signal processing itself are widely discussed. This choice comes from a current tendency of signal processing to use techniques from this field. More than 200 programs and functions are provided in the MATLAB® language, with useful comments and guidance, to enable numerical experiments to be carried out, thus allowing readers to develop a deeper understanding of both the theoretical and practical aspects of this subject.
11185.5 RUR
Johannes Stahl Single Channel Phase-Aware Signal Processing in Speech Communication. Theory and Practice antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
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.
7819.49 RUR
Jacob Benesty Fundamentals of Signal Enhancement and Array Signal Processing antonio napolitano generalizations of cyclostationary signal processing spectral analysis and applications
A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals Systematically introduces the fundamental principles, theory and applications of signal enhancement and array signal processing in an accessible manner Offers an updated and relevant treatment of array signal processing with rigor and concision Features a companion website that includes presentation files with lecture notes, homework exercises, course projects, solution manuals, instructor manuals, and Matlab codes for the examples in the book
10234.67 RUR