noise

Proper way to add noise to signal

可紊 提交于 2019-11-27 07:42:54
In many areas I have found that while adding noise, we mention some specification like zero mean and variance. I need to add AWGN, colored noise, uniform noise of varying SNR in Db. The following code shows the way how I generated and added noise. I am aware of the function awgn() but it is a kind of black box thing without knowing how the noise is getting added. So, can somebody please explain the correct way to generate and add noise. Thank you SNR = [-10:5:30]; %in Db snr = 10 .^ (0.1 .* SNR); for I = 1:length(snr) noise = 1 / sqrt(2) * (randn(1, N) + 1i * randn(1, N)); u = y + noise .* snr

Simulating TV noise

泄露秘密 提交于 2019-11-27 05:08:51
问题 I have googled a bit but was never able to find an answer. What should be my first approach to simulate a video and audio noise from TV on screen? I mean, when my TV antenna is removed but the TV is still on (like they show in Japanese horror movies sometimes). I can use ffmpeg or any other technique but what is the simplest possible form of the signal? 回答1: Create video and audio noise, artifacts, and errors with ffmpeg Noise Using filters The geq (video "generic equation") filter (with

How to use Kalman filter in Python for location data?

若如初见. 提交于 2019-11-27 04:11:20
问题 [EDIT] The answer by @Claudio gives me a really good tip on how to filter out outliers. I do want to start using a Kalman filter on my data though. So I changed the example data below so that it has subtle variation noise which are not so extreme (which I see a lot as well). If anybody else could give me some direction on how to use PyKalman on my data that would be great. [/EDIT] For a robotics project I'm trying to track a kite in the air with a camera. I'm programming in Python and I

Matlab filter electical spikes in accelerometric data

徘徊边缘 提交于 2019-11-26 17:11:55
问题 I have a dataset of accelerometric data that is affected by electical spikes. I'm looking for a good method to filter out or reduce these spikes as need to calculate on these data a rolling window of FFT and other statistical indicators such as kurtosis and skewness. I can't simply delete these outliers or replace them with NaN. Sampling 2000[hz] Until now I've tried on MATLAB 2012b: Wavelet denoising (Haar wavelet) Median Filter Despike and iterpolate approach Can you suggest a proper

Proper way to add noise to signal

删除回忆录丶 提交于 2019-11-26 12:43:00
问题 In many areas I have found that while adding noise, we mention some specification like zero mean and variance. I need to add AWGN, colored noise, uniform noise of varying SNR in Db. The following code shows the way how I generated and added noise. I am aware of the function awgn() but it is a kind of black box thing without knowing how the noise is getting added. So, can somebody please explain the correct way to generate and add noise. Thank you SNR = [-10:5:30]; %in Db snr = 10 .^ (0.1 .*

Gradient Circles for Map Generator

浪尽此生 提交于 2019-11-26 11:54:10
So I'm making a map generator that makes random islands. It uses Perlin Noise at the heart of the generator and then a method using circles with gradients to make the islands. The circle method creates a number of circles in the centerish of the map with a gradient from a colour starting at 64 down to 0. The issue is that this method is creating a un-natrual look at parts of the map with circular edges. When the perlin noise is generated for a pixel it will get that pixel on the gradient map and then mutliply it by the blue value. So if the perlin noise gives a one on pixel 1, 5 and the blue

Gradient Circles for Map Generator

核能气质少年 提交于 2019-11-26 02:59:10
问题 So I\'m making a map generator that makes random islands. It uses Perlin Noise at the heart of the generator and then a method using circles with gradients to make the islands. The circle method creates a number of circles in the centerish of the map with a gradient from a colour starting at 64 down to 0. The issue is that this method is creating a un-natrual look at parts of the map with circular edges. When the perlin noise is generated for a pixel it will get that pixel on the gradient map