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Noise Reduction


Classic book of fundamentals of noise control and noise reduction for the general engineer. Elementary beginnings leading to the advanced aspects of noise reduction for offices, residences, auditoriums and transportation vehicles. Case histories and abundant references.

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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.

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Nakrani Naitik Active Noise Control


Active noise control is one of the popular method involves the use of signal processor which gives better performance compared to passive noise control. An active noise control system removes the primary noise by providing secondary noise which has equal amplitude and opposite phase of the primary noise based on principle of superposition. This system use sensors and digital signal processor to produce anti noise signal by manipulating the error using an adaptive filter. The use of adaptive filter is necessary when the environment is non stationary and it requires minimum priory information of statistical parameters. Depending on the application, lot many active noise control structures have been employed based on different adaptive algorithm. The most popular adaptive algorithm proposed in various literatures for ANC applications is the filtered-x least mean square (FxLMS) algorithm which is a modified version of the LMS. This Dissertation thesis briefly reviews various active noise control structur

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Subramaniam Ganesan Model based design of Adaptive Noise Cancellation


This book demonstrates the implementation of an improved adaptive Wiener filter on Texas Instruments TMS 320C6713 DSK board. A performance comparison of an improved adaptive Wiener filter with Lee's adaptive Wiener filter is illustrated. the profile parameters of the auto-code generated by the Real Time workshop for the Simulink model of LMS filter on TI C6713 DSK is compared with the C implementation of LMS filter on C6713. A LabVIEW model of adaptive noise cancellation based on an improved adaptive Wiener filter is implemented on C6713 using TIDSP Test Integration Tool kit.

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