A randomly chosen text block appears and you try to type as many words from it as possible in the least amount of time. Easily edited code allows for custom texts and times.
The speed and word count measurements aren't perfect, but should give you a 'rough' estimate of how quickly you type.
Mu-Tools based Multivariable System Identification
The Musysid folder contains some useful tools for : - black box MIMO system identification - state space system fitting from a given frequency response - converting...
The variation in Inter-Spike Interval (ISI) between repetitions of a stimulus such as a tone burst for auditory neurons is one of the standard criteria used to classify their responses. The standard method uses bins and produces a noisy and biased...
This Hough transform is highly optimized. It uses the midpoint circle algorithm to draw the circles in voting space quickly and without gaps. It also includes an option for searching only part of the image to increase speed if a rough estimate of...
This program converts the noise sidebands to power, adds in an estimate of the power for CW spurs, then calculates the jitter from this. It is not really exact, but it is simple and allows for an easy estimate of the jitter and phase noise without...
Some curve fitting or smoothing tools can benefit from knowledge of the noise variance to expect on your data. Kalman filters use this information, also some spline fitting tools. So I wrote a function to extract the noise variance from a signal...
Provides a search tab which pulls results from the Bing web service. The search query can be limited to a set of sites, and various advanced search query strings can be used (or appended to all search queries).
The 1.x branch of this...
Function accepts size distribution in the form of two vectors: mesh size (d) and cumulative percent material retained R(d).
Example: d = [0.08 0.50 1.25 2 4 6.3 8 12.5 16 40] Rd = [95.61 87.71 82.45 79.78 73.28 66.98 63.21...
I need to thank Duane Hanselman for suggesting this great idea.
Fminspleas is a simple nonlinear least squares tool that fits regression models of the form
Y = a1*f1(X,C) + a2*f2(X,C) + ... + an*fn(X,C)
X can be...
About the GAME:
Objective: To estimate the Space-Filling Curve's Area? Hint: Space-Filling Curve connects all the points.
Suppose that you have a signal Y (Y can be a time series, a parametric surface or a volumetric data series) corrupted by a Gaussian noise with unknown variance. It is often of interest to know more about this variance. EVAR(Y) thus returns an...
Bivariate Kamma Kernel Density Estimate for large data set
Matlab implementation of an MMSE based noise PSD tracking algorithm for speech enhancement. This package is an implementation of the algorithm described in "MMSE BASED NOISE PSD TRACKING WITH LOW COMPLEXITY", by Richard C. Hendriks,...
09 Mar 2008 (Updated 08 Apr 2010)
An estimate of probability density function of the given random data with bounded support.
udeconv - Unsupervised Wiener-Hunt deconvolution
[xEap, gnChain, gxChain] = udeconv(data, ir, reg, criterion, burnin, maxIter)
return the deconvolution of 'data' by 'ir' with the 'reg' regularization operator. The algorithm...
The zip file contains functions to calculate an Ambiguity Function (XAMB), Upsampled and Interpolated Correlation (XCORRU), and Coherence Function (XCOH). A prefilter can be specified in each function to "sharpen" correlation peaks.
This script implements the linear Kalman filter and shows its performance on a 2nd order under-damped LTI system.
The code consists of two main parts. In the first part, a noisy model with two state variables is simulated and in the...
Compute estimate Peak Sidelobe Level and Integrated Sidelobe Level and Merit Factorofat at different complex communication signals of their Autocorrelation function and in case partially minimize bounds on the volume of ambiguity function.In base...
The attached Matlab file estimate numerically the probability of error for M-array orthogonal signals and plot the graph BER for M-signals [2 to 64].
Numerical estimation is performed on the probability of error equation derived in...
A Dynamic environment is one in which either the obstacles or the goal or both are in motion. In most of the current research, robots attempting to navigate in dynamic environments use reactive systems. Although reactive systems have the advantage... |