Frequency Content and Autocorrelation Function of Noisy Periodic Signals
نویسندگان
چکیده
We extract the frequency content of a noisy signal by use of Discrete Fourier Transform. Our analysis overcomes the limitations imposed by incommensurate lattices. After computing the deterministic component, we show the relevance of the method in removing spurious autocorrelations from the signal residuals. Results are presented for a temperature time series.
منابع مشابه
Adaptive Optimum Notch Filter for Periodic Noise Reduction in Digital Images
Periodic noises are unwished and spurious signals that create repetitive pattern on images and decreased the visual quality. Firstly, this paper investigates various methods for reducing the effects of the periodic noise in digital images. Then an adaptive optimum notch filter is proposed. In the proposed method, the regions of noise frequencies are determined by analyzing the spectral of noisy...
متن کاملبررسی وضعیت شنوایی کارگران کارگاههای پر سروصدای کارخانه آزمایش تهران
Background : Noise-induced hearing loss is among the most common cause of occupational-related hearing loss. Nowadays, noise-induced hearing loss is a disastrous event of industrial world that may influence all races, ethnics and age groups. Methods : This cross sectional study was performed on 100 workers exposed to noisy environment (greater 85db) in Azmayesh factory. Having excluded all con...
متن کاملRobust pitch estimation in noisy speech using ZTW and group delay function
Identification of pitch for speech signals recorded in noisy environments is a fundamental and long persistent problem in speech research. Several time domain based techniques attempt to exploit the periodic nature of the waveform using autocorrelation function and its variants. Other set of techniques utilize the harmonic structure in the spectral domain to identify pitch values. Either of the...
متن کاملAbout periodicity and signal to noise ratio - The strength of the autocorrelation function
In condition monitoring a part of the information necessary for decision-making comes from scrutinizing a time measure or a transform of this measure. Frequency domain is commonly exploited; lag domain is not, albeit advantages of the autocorrelation function have long been known. In this paper, we dwell on the autocorrelation function in order to extract some interesting properties of the meas...
متن کاملSystem Identification Based on Frequency Response Noisy Data
In this paper, a new algorithm for system identification based on frequency response is presented. In this method, given a set of magnitudes and phases of the system transfer function in a set of discrete frequencies, a system of linear equations is derived which has a unique and exact solution for the coefficients of the transfer function provided that the data is noise-free and the degrees of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003