MATLAB Central - Fast XYZ regular grid data to Matrix. What are newsgroups? The newsgroups are a worldwide forum that is open to everyone. Newsgroups are used to discuss a huge range of topics, make announcements, and trade files. Discussions are threaded, or grouped in a way that allows you to read a posted message and all of its replies in chronological order. This makes it easy to follow the thread of the conversation, and to see what’s already been said before you post your own reply or make a new posting. Newsgroup content is distributed by servers hosted by various organizations on the Internet. Messages are exchanged and managed using open-standard protocols. No single entity “owns” the newsgroups. There are thousands of newsgroups, each addressing a single topic or area of interest. How do I read or post to the newsgroups? MATLAB Central You can use the integrated newsreader at the MATLAB Central website to read and post messages in this newsgroup. One Account Your MATLAB Central account is tied to your MathWorks Account for easy access.
MATLAB Central - Calculate distance between many points and one cer... What are newsgroups? The newsgroups are a worldwide forum that is open to everyone. Newsgroups are used to discuss a huge range of topics, make announcements, and trade files. Discussions are threaded, or grouped in a way that allows you to read a posted message and all of its replies in chronological order. This makes it easy to follow the thread of the conversation, and to see what’s already been said before you post your own reply or make a new posting. Newsgroup content is distributed by servers hosted by various organizations on the Internet. Messages are exchanged and managed using open-standard protocols. No single entity “owns” the newsgroups. There are thousands of newsgroups, each addressing a single topic or area of interest.
How do I read or post to the newsgroups? MATLAB Central You can use the integrated newsreader at the MATLAB Central website to read and post messages in this newsgroup. One Account Your MATLAB Central account is tied to your MathWorks Account for easy access. Matlab / Octave efficiency notes. In March 2011 I was asked to provide a short tutorial on “writing efficient Matlab code”. Here are some notes from that tutorial, including some notes on good practice that don’t strictly relate to efficiency. For more detail, see some of this recommended reading: Opening Quiz Here are some things to think about. How would you sample, uniformly at random, K values from a list of N values without replacement? You have a large NxD data array data, (with N=1e7 say). Meta-question: (When) should we care about questions like these? My answers are below, but the questions will be more useful if you think about them for yourself first. Contents When (not) to use Matlab and Octave Data types and structures: In the beginning, MATLAB the “MATrix LABoratory” had one data-type: a matrix of doubles.
Historically, complex data-structures haven’t been easy or efficient in Matlab. Free vs Proprietary: Octave is Free Software, whereas Matlab is closed source, cannot be modified and costs money. Vectorization. What is wrong in this 1/3 Octave analysis procedure? - MATLAB Answers. Hi dears, Good Morning!
I am new in signal processing and I am trying to do a work in noise control of an electronic steering lock device (ESL). My aim is to calculate the loudness (Zwicker Method- ISO 532 B) of this device. To do so, first I need to obtain the 1/3 octave spectrum of a time signal that I measure with a microphone. The problem is I keep getting negative values in dB for the 1/3 Octave bands after filtering the signal in the time domain to obtain the spectrum.
I have done the following procedure by now: 1- Sampled the noise signal (impulsive noise) by using a microphone and a data logger (to record the data), which has a sample frequency of 50K Hz. 2- I get the vector INPUT (with 250000 points of pressure (Pa)-measurements of 5s) and use a function in matlab, in order to filter the signal in each each 1/3 octave band. 3- Then, the program calculates the rms value of the OUTPUT (after filtering). Does anybody know what i am doing wrong? Sound Power Directivity Analysis. File Exchange. Code covered by the BSD License Highlights from Sound Power Directivity Analysis Directivity_Analysis_Tayl...% Directivity_Analysis_Taylor2: Calculate sound Power Measurement integration error using directivity analysis LMSloc(X) Taylor_dev_2d(data, xi, y...% Taylor_dev_2d: Calculates Taylor series over a hemisphere Taylor_terms_2d2(data, u1...% Taylor_terms_2d2: Calculates the terms for the Taylor Series over a hemisphere.
Allstats(x,dim,flag,p)ALLSTATS All Common Statistics. Derivative_calcs(ZI, ZI_b...% derivative_calcs: Calculates many derivatives dev_re_edge(f, x, y, z, p...% dev_re_edge: Truncates and smoothes the values of the data near the edge of the distribution. Dipole(f, r, x0, y0, z0, ...% dipole: Unit dipole source with ISO measurement point spacing dipole2(f, r, x0, y0, z0,...% dipole2: Unit dipole source with equal angular spacing. Dipole3(f, r, x0, y0, z0,...% dipole2: Unit dipole source with Gauss quadrature angular spacing. Contact us. Cross power spectral density - MATLAB cpsd. Pxy = cpsd(x,y) estimates the cross power spectral density, Pxy, of two discrete-time signals, x and y, using Welch's averaged, modified periodogram method of spectral estimation.
The input signals may be either vectors or two-dimensional matrices. If both are vectors, they must have the same length. If both are matrices, they must have the same size, and cpsd operates columnwise: Pxy(:,n) = cpsd(x(:,n),y(:,n)). If one is a matrix and the other is a vector, then the vector is converted to a column vector and internally expanded so both inputs have the same number of columns. For real x and y, cpsd returns a one-sided CPSD and for complex x or y, it returns a two-sided CPSD. cpsd uses the following default values: Pxy = cpsd(x,y,window) specifies a windowing function, divides x and y into overlapping sections of the specified window length, and windows each section using the specified window function.
. [...] = cpsd(... cpsd(...) plots the CPSD versus frequency in the current figure window. MATLAB Central - Signal filtering and DELAY. What are newsgroups? The newsgroups are a worldwide forum that is open to everyone. Newsgroups are used to discuss a huge range of topics, make announcements, and trade files. Discussions are threaded, or grouped in a way that allows you to read a posted message and all of its replies in chronological order. This makes it easy to follow the thread of the conversation, and to see what’s already been said before you post your own reply or make a new posting. Newsgroup content is distributed by servers hosted by various organizations on the Internet. Messages are exchanged and managed using open-standard protocols. No single entity “owns” the newsgroups. There are thousands of newsgroups, each addressing a single topic or area of interest.
How do I read or post to the newsgroups? MATLAB Central You can use the integrated newsreader at the MATLAB Central website to read and post messages in this newsgroup. One Account Your MATLAB Central account is tied to your MathWorks Account for easy access. Processing audio samples while recording in matlab. AFMG Network :: View topic - Creating Speaker Data XHN Files. Creating an EASE Speaker Data File - MTI Ses Danışmanlığı. ResolutionFront=input('Front side theta resolution for measurements: '); existRear=0; resolutionRear=2*resolutionFront; axissymmetry=input('Does axial symmetry exist? (0 or 1): '); if axissymmetry == 0 resolutionPsi=input('Psi resolution for measurements: '); symmetryHorizontal=input('Horizontal Symmetry? SymmetryVertical=input('Vertical Symmetry? Else resolutionPsi=90;symmetryHorizontal=1;symmetryVertical=1; end disp(' ') disp('Which frequencies will be measured?
') freqs=input('Enter vector data or press Enter for EASE defaults: '); if isempty(freqs), freqs=[100 125 160 200 250 315 400 500 630 800 1000 1250 1600 2000 2500 3150 4000 5000 6300 8000 10000];end exp.resolution=5; dataInputByHand=input('Input data by hand? DoAmpCalibration=input('Do amplifier calibration? Nfreqs=length(freqs); if existRear==1,exp.theta = (0:exp.resolution:180)'; else exp.theta = (0:exp.resolution:90)'; end exp.psi = 0:exp.resolution:360-exp.resolution; if existRear==1, meas.theta = [0:resolutionFront:90]'; pause,end end,end,
Real spectrum analysis with Octave and MATLAB. Store or retrieve UI data - MATLAB guidata. Description guidata(object_handle,data) stores the variable data with the object specified by object_handle. If object_handle is not a figure, then the object's parent figure is used. data can be any MATLAB® variable, but is typically a structure, which enables you to add new fields as required. guidata can manage only one variable at any time. Subsequent calls to guidata(object_handle,data) overwrite the previously stored data. data = guidata(object_handle) returns previously stored data, or an empty matrix if nothing is stored.
To change the data managed by guidata: Get a copy of the data with the command data = guidata(object_handle).Make the desired changes to data.Save the changed version of data with the command guidata(object_handle,data). guidata provides application developers with a convenient interface to a figure's application data: Examples Using guidata in a Programmatic UI Calling the guihandles function creates the structure into which your code places additional data. Demo files for "Parallel Computing with MATLAB" Webinar. Features - DSP System Toolbox. Key Features Streaming signal processing in MATLAB and frame-based signal processing in Simulink DSP algorithms optimized for implementation and deployment to hardware Filter design tools and implementation for FIR, IIR, multistage, multirate, and adaptive filters such as parametric equalizer, Polyphase, CIC, Farrow, and LMS Time Scope, Spectrum Analyzer, and Logic Analyzer with measurements including THD, SNR, peak finder, min-max hold, and harmonic analysis Multichannel real-time audio processing and I/O including support for ASIO drivers and MIDI controls Support for fixed-point modeling, HDL code generation, and C-code generation including optimization for ARM Cortex processors Audio equalization using parametric equalizer (EQ) filters.
MATLAB code (top left), with UI for parameter tuning in real time for audio processing in MATLAB on the desktop (top right), parametric filter magnitude response (bottom right), and equivalent Simulink model (bottom left). Multirate Systems. Frequency Response. Digital Domain freqz uses an FFT-based algorithm to calculate the z-transform frequency response of a digital filter. Specifically, the statement [h,w] = freqz(b,a,p) returns the p-point complex frequency response, H(ejω), of the digital filter. In its simplest form, freqz accepts the filter coefficient vectors b and a, and an integer p specifying the number of points at which to calculate the frequency response. freqz returns the complex frequency response in vector h, and the actual frequency points in vector w in rad/s. freqz can accept other parameters, such as a sampling frequency or a vector of arbitrary frequency points. The example below finds the 256-point frequency response for a 12th-order Chebyshev Type I filter.
[b,a] = cheby1(12,0.5,200/500); [h,f] = freqz(b,a,256,1000); Because the parameter list includes a sampling frequency, freqz returns a vector f that contains the 256 frequency points between 0 and fs/2 used in the frequency response calculation. freqz(b,a,256,2000) Delay.