close all; clear all; clc; filename = 'imu.csv'; data = load_IMU_data_from_csv( filename ) ; t = data.t; ax = data.ax; ay = data.ay; az = data.az; gx = data.gx; gy = data.gy; gz = data.gz; % analyze the noise (deviation from mean) on each axis and compare the % emperical distribution to one generated from a quantized Gaussian % distrubtuion with the same variance. quantized_noise_gauss_anal( ax , 'Accelerometer' , 'x-axis' , 'gs' ) quantized_noise_gauss_anal( ay , 'Accelerometer' , 'y-axis', 'gs' ) quantized_noise_gauss_anal( az , 'Accelerometer' , 'z-axis', 'gs' ) quantized_noise_gauss_anal( gx , 'Gyroscope' , 'x-axis' , 'rad/s') quantized_noise_gauss_anal( gy , 'Gyroscope' , 'y-axis' , 'rad/s' ) quantized_noise_gauss_anal( gz , 'Gyroscope' , 'z-axis' , 'rad/s' )