noise

Is there a (legal) way to capture the ENTIRE screen under iOS?

筅森魡賤 提交于 2019-12-01 18:15:50
I've tried several techniques to capture a screenshot of an app from within that app. None of the techniques appear to capture the status bar -- it ends up being black. There apparently was once a way to do this, but that interface is internal and Apple will not let you use it. Any ideas? Note: This is an attempt to solve this problem , where I need to determine if airplane mode is on or off (and no, simply knowing if the network is reachable is not sufficient). However, it would seem that this question is of more general interest, and is distinct from that question. Your actual issue,

Is there a (legal) way to capture the ENTIRE screen under iOS?

回眸只為那壹抹淺笑 提交于 2019-12-01 18:02:05
问题 I've tried several techniques to capture a screenshot of an app from within that app. None of the techniques appear to capture the status bar -- it ends up being black. There apparently was once a way to do this, but that interface is internal and Apple will not let you use it. Any ideas? Note: This is an attempt to solve this problem, where I need to determine if airplane mode is on or off (and no, simply knowing if the network is reachable is not sufficient). However, it would seem that

Generate white noise with amplitude between [-1 1] with Matlab

不羁的心 提交于 2019-12-01 11:46:09
I'm using the Matlab function Y = WGN(M,N,P) to generate white noise with Gaussian distribution. This function uses a power value (dB Watts) to calculate the amplitude of the output signal. Since I want to get an output amplitude range of -1 V to 1 V there is a function mode 'linear'. I'm trying to use the 'linear' mode to produce the output but the result is an output amplitude range of [-4 4] RandomSignal = wgn(10000,1,1,1,'linear'); Time = linspace(0,10,10000); figure() plot(Time,RandomSignal) figure() hist(RandomSignal,100) Is there another function to produce this result, or am I just

How to add 5% percent Gaussian noise to image

不问归期 提交于 2019-12-01 06:37:36
问题 let define that: The "percent noise" number represents the percent ratio of the standard deviation of the white Gaussian noise versus the signal for whole image. Assume I have a brain image, I want to add 5% Gaussian noise to whole image (tissues) by Matlab code: I=imread('brain91.png'); I=rgb2gray(I);I=double(I); I = I - min(I(:)); I = I / max(I(:)); %// Add noise to image v = 0.05*var(I(:)); I_noisy = imnoise(I, 'gaussian', 0, v); I_noisy=255.*I_noisy; subplot(121);imshow(I,[]);subplot(122)

Reduce the volume of a Wav audio file using C

怎甘沉沦 提交于 2019-12-01 01:50:39
I am writing a C program for editing a Wav audio file. I have loaded all file datas in an array of unsigned integer values (UINT16_T). Now, i would like to reduce the volume of the file. I thought it was enough to decrease the value (of a certain percentage) of the single values. But if i do that, i obtain an audio file with noise (I think I understand is called "static" or "click noise") Why? Which is the right procedure? Thank You! This is the piece of code affected: FILE* fp; FILE* fp2; /*Size of my file*/ #define BUFFER_SIZE 28242852 /*Array with file data*/ unsigned char *buffer; /*Array

Reduce the volume of a Wav audio file using C

空扰寡人 提交于 2019-11-30 20:09:41
问题 I am writing a C program for editing a Wav audio file. I have loaded all file datas in an array of unsigned integer values (UINT16_T). Now, i would like to reduce the volume of the file. I thought it was enough to decrease the value (of a certain percentage) of the single values. But if i do that, i obtain an audio file with noise (I think I understand is called "static" or "click noise") Why? Which is the right procedure? Thank You! This is the piece of code affected: FILE* fp; FILE* fp2; /

Add noise effect to a drawing

丶灬走出姿态 提交于 2019-11-30 16:35:15
I'm in the process of creating a custom view for my android application and would like to add a noise overlay over my drawings. My drawings are pretty standard, arcs, bezier curves, etc. What would be the way to go with creating a noise overlay over arbitrary shapes, drawn with canvas? Use a tileable transparent noise png and cover the canvas with it. 来源: https://stackoverflow.com/questions/6994289/add-noise-effect-to-a-drawing

Why does switching from Mersenne twister to other PRNGs in Gradient Noise Generator give bad results?

社会主义新天地 提交于 2019-11-30 15:49:14
问题 I've been trying to create a generalized Gradient Noise generator (which doesn't use the hash method to get gradients). The code is below: class GradientNoise { std::uint64_t m_seed; std::uniform_int_distribution<std::uint8_t> distribution; const std::array<glm::vec2, 4> vector_choice = {glm::vec2(1.0, 1.0), glm::vec2(-1.0, 1.0), glm::vec2(1.0, -1.0), glm::vec2(-1.0, -1.0)}; public: GradientNoise(uint64_t seed) { m_seed = seed; distribution = std::uniform_int_distribution<std::uint8_t>(0, 3);

Why does switching from Mersenne twister to other PRNGs in Gradient Noise Generator give bad results?

别来无恙 提交于 2019-11-30 15:14:28
I've been trying to create a generalized Gradient Noise generator (which doesn't use the hash method to get gradients). The code is below: class GradientNoise { std::uint64_t m_seed; std::uniform_int_distribution<std::uint8_t> distribution; const std::array<glm::vec2, 4> vector_choice = {glm::vec2(1.0, 1.0), glm::vec2(-1.0, 1.0), glm::vec2(1.0, -1.0), glm::vec2(-1.0, -1.0)}; public: GradientNoise(uint64_t seed) { m_seed = seed; distribution = std::uniform_int_distribution<std::uint8_t>(0, 3); } // 0 -> 1 // just passes the value through, origionally was perlin noise activation double

First random number after setSeed in Java always similar

﹥>﹥吖頭↗ 提交于 2019-11-30 13:35:47
问题 To give some context, I have been writing a basic Perlin noise implementation in Java, and when it came to implementing seeding, I had encountered a bug that I couldn't explain. In order to generate the same random weight vectors each time for the same seed no matter which set of coordinates' noise level is queried and in what order, I generated a new seed ( newSeed ), based on a combination of the original seed and the coordinates of the weight vector, and used this as the seed for the