White noise: A time domain basis

Abstract

Time domain definitions for finite bandwidth white noise, and filtered white noise, are detailed and are of pedagogical value. The associated power spectral density and autocorrelation functions are given. The potential Gaussianity of white noise is noted.

Implementación y ensayo de un demodulador FSK

“…Para la simulación se generó, con ayuda de una herramienta matemática, una señal modulada en FSK1200 con diferentes niveles de SNR (Relación Señal Ruido), agregando ruido blanco Gaussiano [12]. Dicha señal se cargó en una tabla, dentro del hardware descripto, y se la recorrió con un contador mientras se alimentaba al demodulador, como se puede apreciar en la Fig.…”

Comparison of noise and chirp waveforms for radar target detection in clutter

“…By using a Poisson distribution to select a random number of frequencies for each time period, different length time periods can be approximated. From the central limit theorem, it can be shown that for a large number of samples, the approximations approach Gaussian band‐limited noise [27].…”

“…While the above method does yield a band‐limited signal, it requires further filtering around the frequency range of interest. By maintaining the maximum frequency to be much larger than the signal bandwidth of interest, the auto‐correlation properties better approximate an ideal delta function over the integration times corresponding to the signal bandwidth [27]. For the work detailed in Sections 3 and 4, the frequency band of interest was 2.5–3.5 GHz, and so the sampling frequency was chosen to be 15 GHz, thus meeting the necessary criterion of being much larger than the 1 GHz bandwidth.…”

Vehicular networking and computer vision-based distance estimation for VANET application using Raspberry Pi 3

“…Since the nature of the cascade classifier applied extensive numbers of Haar feature by sizes and shapes [10] in sliding window, the results produced resembles a random process which generates a stationary white noise added to the measurement, this part intended to investigate the characteristic of the noise whether it is white or not and to see if optimum Kalman filter can be exploited. White noise defined as a series of uncorrelated random variables following a continues distribution with zero mean and unity variance also a process is a white noise if its close-spaced time series sample is uncorrelated [18], moreover, if those samples were independent, it follows Gaussian distribution hence guaranteed for randomness.…”