TAILIEUCHUNG - Advanced DSP and Noise reduction P15

CHANNEL EQUALIZATION AND BLIND DECONVOLUTION Introduction Blind-Deconvolution Using Channel Input Power Spectrum Equalization Based on Linear Prediction Models Bayesian Blind Deconvolution and Equalization Blind Equalization for Digital Communication Channels Equalization Based on Higher-Order Statistics Summary lind deconvolution is the process of unravelling two unknown signals that have been convolved. An important application of blind deconvolution is in blind equalization for restoration of a signal distorted in transmission through a communication channel. Blind equalization has a wide range of applications, for example in digital telecommunications for removal of intersymbol interference, in speech recognition for removal of. | Advanced Digital Signal Processing and Noise Reduction Second Edition. Saeed V. Vaseghi Copyright 2000 John Wiley Sons Ltd ISBNs 0-471-62692-9 Hardback 0-470-84162-1 Electronic 15 CHANNEL EQUALIZATION AND BLIND DECONVOLUTION Introduction Blind-Deconvolution Using Channel Input Power Spectrum Equalization Based on Linear Prediction Models Bayesian Blind Deconvolution and Equalization Blind Equalization for Digital Communication Channels Equalization Based on Higher-Order Statistics Summary Blind deconvolution is the process of unravelling two unknown signals that have been convolved. An important application of blind deconvolution is in blind equalization for restoration of a signal distorted in transmission through a communication channel. Blind equalization has a wide range of applications for example in digital telecommunications for removal of intersymbol interference in speech recognition for removal of the effects of microphones and channels in deblurring of distorted images in dereverberation of acoustic recordings in seismic data analysis etc. In practice blind equalization is only feasible if some useful statistics of the channel input and perhaps also of the channel itself are available. The success of a blind equalization method depends on how much is known about the statistics of the channel input and how useful this knowledge is in the channel identification and equalization process. This chapter begins with an introduction to the basic ideas of deconvolution and channel equalization. We study blind equalization based on the channel input power spectrum equalization through separation of the input signal and channel response models Bayesian equalization nonlinear adaptive equalization for digital communication channels and equalization of maximum-phase channels using higher-order statistics. Introduction 417 Introduction In this chapter we consider the recovery of a signal distorted in transmission through a .

TÀI LIỆU LIÊN QUAN
31    426    56
TỪ KHÓA LIÊN QUAN
TAILIEUCHUNG - Chia sẻ tài liệu không giới hạn
Địa chỉ : 444 Hoang Hoa Tham, Hanoi, Viet Nam
Website : tailieuchung.com
Email : tailieuchung20@gmail.com
Tailieuchung.com là thư viện tài liệu trực tuyến, nơi chia sẽ trao đổi hàng triệu tài liệu như luận văn đồ án, sách, giáo trình, đề thi.
Chúng tôi không chịu trách nhiệm liên quan đến các vấn đề bản quyền nội dung tài liệu được thành viên tự nguyện đăng tải lên, nếu phát hiện thấy tài liệu xấu hoặc tài liệu có bản quyền xin hãy email cho chúng tôi.
Đã phát hiện trình chặn quảng cáo AdBlock
Trang web này phụ thuộc vào doanh thu từ số lần hiển thị quảng cáo để tồn tại. Vui lòng tắt trình chặn quảng cáo của bạn hoặc tạm dừng tính năng chặn quảng cáo cho trang web này.