tailieunhanh - Báo cáo hóa học: " Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation | EURASIP Journal on Applied Signal Processing 2004 12 1791-1806 2004 Hindawi Publishing Corporation Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation S. Chandra Sekhar Department of Electrical Communication Engineering Indian Institute of Science Bangalore 560 012 India Email schash@ T. V. Sreenivas Department of Electrical Communication Engineering Indian Institute of Science Bangalore 560 012 India Email tvsree@ Received 2 September 2003 Revised 2 March 2004 We address the problem of estimating instantaneous frequency IF of a real-valued constant amplitude time-varying sinusoid. Estimation of polynomial IF is formulated using the zero-crossings of the signal. We propose an algorithm to estimate nonpolynomial IF by local approximation using a low-order polynomial over a short segment of the signal. This involves the choice of window length to minimize the mean square error MSE . The optimal window length found by directly minimizing the MSE is a function of the higher-order derivatives of the IF which are not available a priori. However an optimum solution is formulated using an adaptive window technique based on the concept of intersection of confidence intervals. The adaptive algorithm enables minimum MSE-IF MMSE-IF estimation without requiring a priori information about the IF. Simulation results show that the adaptive window zero-crossing-based IF estimation method is superior to fixed window methods and is also better than adaptive spectrogram and adaptive Wigner-Ville distribution WVD -based IF estimators for different signal-to-noise ratio SNR . Keywords and phrases zero-crossing irregular sampling instantaneous frequency bias-variance tradeoff confidence interval adaptation. 1. INTRODUCTION Almost all information carrying signals are time-varying in nature. The adjective time-varying is used to describe an attribute of the signal that is changing evolving in time 1 . For most signals such as .