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  • Using Cepstrum for PDA

    - by CziX
    Hey, I am currently deleveloping a algorithm to decide wheather or not a frame is voiced or unvoiced. I am trying to use the Cepstrum to discriminate between these two situations. I use MATLAB for my implementation. I have some problems, saying something generally about the frame, but my currently implementation looks like (I'm award of the MATLAB has the function rceps, but this haven't worked for either): ceps = abs(ifft(log10(abs(fft(frame.*window')).^2+eps))); Can anybody give me a small demo, that will convert the frame to the power cepstrum, so a single lollipop at the pitch frequency. For instance use this code to generate the frequency. fs = 8000; timelength = 25e-3; freq = 500; k = 0:1/fs:timelength-(1/fs); s = 0.8*sin(2*pi*freq*k); Thanks.

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  • side effect gotchas in python/numpy? horror stories and narrow escapes wanted

    - by shabbychef
    I am considering moving from Matlab to Python/numpy for data analysis and numerical simulations. I have used Matlab (and SML-NJ) for years, and am very comfortable in the functional environment without side effects (barring I/O), but am a little reluctant about the side effects in Python. Can people share their favorite gotchas regarding side effects, and if possible, how they got around them? As an example, I was a bit surprised when I tried the following code in Python: lofls = [[]] * 4 #an accident waiting to happen! lofls[0].append(7) #not what I was expecting... print lofls #gives [[7], [7], [7], [7]] #instead, I should have done this (I think) lofls = [[] for x in range(4)] lofls[0].append(7) #only appends to the first list print lofls #gives [[7], [], [], []] thanks in advance

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  • An efficient code to determine if a set is a subset of another set

    - by Edward
    I am looking for an efficient way to determine if a set is a subset of another set in Matlab or Mathematica. Example: Set A = [1 2 3 4] Set B = [4 3] Set C = [3 4 1] Set D = [4 3 2 1] The output should be: Set A Sets B and C belong to set A because A contains all of their elements, therefore, they can be deleted (the order of elements in a set doesn't matter). Set D has the same elements as set A and since set A precedes set D, I would like to simply keep set A and delete set D. So there are two essential rules: 1. Delete a set if it is a subset of another set 2. Delete a set if its elements are the same as those of a preceding set My Matlab code is not very efficient at doing this - it mostly consists of nested loops. Suggestions are very welcome! Additional explanation: the issue is that with a large number of sets there will be a very large number of pairwise comparisons.

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  • Different function returns from command line and within function

    - by Myx
    Hello: I have an extremely bizzare situation: I have a function in MATLAB which calls three other main functions and produces two figures for me. The function reads in an input jpeg image, crops it, segments it using kmeans clustering, and outputs 2 figures to the screen - the original image and the clustered image with the cluster centers indicated. Here is the function in MATLAB: function [textured_avg_x photo_avg_x] = process_database_images() clear all warning off %#ok type_num_max = 3; % type is 1='texture', 2='graph', or 3='photo' type_num_max = 1; img_max_num_photo = 100; % 400 photo images img_max_num_other = 100; % 100 textured, and graph images for type_num = 1:2:type_num_max if(type_num == 3) img_num_max = img_max_num_photo; else img_num_max = img_max_num_other; end img_num_max = 1; for img_num = 1:img_num_max [type img] = load_image(type_num, img_num); %img = imread('..\images\445.jpg'); img = crop_image(img); [IDX k block_bounds features] = segment_image(img); end end end The function segment_image first shows me the color image that was passed in, performs kmeans clustering, and outputs the clustered image. When I run this function on a particular image, I get 3 clusters (which is not what I expect to get). When I run the following commands from the MATLAB command prompt: >> img = imread('..\images\texture\1.jpg'); >> img = crop_image(img); >> segment_image(img); then the first image that is displayed by segment_image is the same as when I run the function (so I know that the clustering is done on the same image) but the number of clusters is 16 (which is what I expect). In fact, when I run my process_database_images() function on my entire image database, EVERY image is evaluated to have 3 clusters (this is a problem), whereas when I test some images individually, I get in the range of 12-16 clusters, which is what I prefer and expect. Why is there such a discrepancy? Am I having some syntax bug in my process_database_images() function? If more code is required from me (i.e. segment_images function, or crop_image function), please let me know. Thanks.

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  • Code coordinates to match compass bearings

    - by pinnacler
    Right now in Matlab (0,0) is the origin, 0 degrees / 2pi would be to the right of the cartesian plane and angles are measured counter clockwise with 90 degrees being at the top. I'm trying to write a simulator where the coordinates would match a compass bearing. 0/360 degrees or 2pi would be at the top and 90 degrees would be on the right. Any idea how to code in Matlab or c++? I'd imaging it'd be a matrix flipped about the x axis and rotated 90 degrees but I'm at a total loss. Phil

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  • An efficient code to determine if a set is a subset of another set

    - by Edward
    I am looking for an efficient way to determine if a set is a subset of another set in Matlab or Mathematica. Example: Set A = [1 2 3 4] Set B = [4 3] Set C = [3 4 1] Set D = [4 3 2 1] The output should be: Set A Sets B and C belong to set A because A contains all of their elements, therefore, they can be deleted (the order of elements in a set doesn't matter). Set D has the same elements as set A and since set A precedes set D, I would like to simply keep set A and delete set D. So there are two essential rules: 1. Delete a set if it is a subset of another set 2. Delete a set if its elements are the same as those of a preceding set My Matlab code is not very efficient at doing this - it mostly consists of nested loops. Suggestions are very welcome! Additional explanation: the issue is that with a large number of sets there will be a very large number of pairwise comparisons.

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  • Does a Category applied to NSString also apply to NSCFString via the "toll-free bridge"?

    - by half_brick
    We're integrating a library into an iPhone app which appears to use the google toolbox for iPhone internally. The google toolbox adds a method gtm_stringBySanitizingAndEscapingForXML to NSString. The problem is, whenever we attempt to make a call to this library we get [NSCFString gtm_stringBySanitizingAndEscapingForXML]: unrecognized selector sent to instance 0x272478 So it appears the library is calling that method on a NSCFString, to which the category does not apply. So... is it the case that the category will not apply across the toll-free bridge to CoreFoundation classes? If that's the case then we at least know why it's blowing up. Figuring out how to fix it is a different matter.

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  • How do I interpolate between points without going beyond them?

    - by user1774893
    I have data of variable lengths (reaching movements recorded in 2D) and want to create a function that will resample this data to a uniform length (500 samples). However, I want matlab to only resample between the maximum and minimum values given, without adding any additional distance. For instance, if I resample the matrix [1:1:10], the resampled matrix should have a minimum value of 1 and a maximum value of 10. So far I've tried the following: x = [1:1:10]; interp(x, 500 / length(x)); This, however, gives values above my maximum specified value of 10. Is there any way I can get matlab to resample/interpolate solely between two points, without extending beyond them?

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  • eliminating noise/spikes

    - by tgv
    I have a measurement data with similar positive and negative values which should be like: ReqData=[0 0 -2 -2 -2 -2 -2 -2 0 0 0 -2 -2 -2 -2 0 0 2 2 2 2 2 2 0 0 2 2 2 2 2 0 0 2 2 2 2 2 0 0 2 2 2 0 0]' However, there are some measurement noises in the data - so the real data is like this: RealData=[0 0 -2 -2 -2 -2 -2 -2 0 0 0 -2 -2 -2 -2 0 0 2 2 2 2 -4 -1 0 0 2 2 2 2 -7 0 0 2 2 2 2 -1 0 0 2 2 2 0 0]' How do I remove the end noise from the RealData and convert it into ReqData using Matlab? How do I find the start and stop indexes of each set of positive or negative data and split them using Matlab? For instance, ansPositive = [3,8, 12, 15]' and ansNegative = [18, 23, 26, 30, 33, 37, 40, 42]'.

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  • What is most efficient way of setting row to zeros for a sparce scipy matrix?

    - by Alex Reinking
    I'm trying to convert the following MATLAB code to Python and am having trouble finding a solution that works in any reasonable amount of time. M = diag(sum(a)) - a; where = vertcat(in, out); M(where,:) = 0; M(where,where) = 1; Here, a is a sparse matrix and where is a vector (as are in/out). The solution I have using Python is: M = scipy.sparse.diags([degs], [0]) - A where = numpy.hstack((inVs, outVs)).astype(int) M = scipy.sparse.lil_matrix(M) M[where, :] = 0 # This is the slowest line M[where, where] = 1 M = scipy.sparse.csc_matrix(M) But since A is 334863x334863, this takes like three minutes. If anyone has any suggestions on how to make this faster, please contribute them! For comparison, MATLAB does this same step imperceptibly fast. Thanks!

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  • Autocommands for Matlab in vim?

    - by Benjamin Oakes
    I use several different programming languages every day, and I'd like to have different tab widths (in spaces) for each. For example: I use the "standard" 2 spaces for Ruby, but all our existing Matlab code uses 4 spaces. I have this from my personal ~/.vimrc: augroup lang_perl au! set tabstop=4 " tabstop length N in spaces set shiftwidth=4 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END augroup lang_ruby au! set tabstop=2 " tabstop length N in spaces set shiftwidth=2 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END Those work, but the following doesn't: augroup lang_matlab au! set tabstop=4 " tabstop length N in spaces set shiftwidth=4 " make >> and friends (<<, ^T, ^D) shift N, not the default 8 set expandtab " Use spaces instead of tabs augroup END I really don't understand how augroup lang_ruby figures out that I'm editing a Ruby file. (My searches brought up ftdetect, but the solution wasn't obvious.) It doesn't seem like vim knows that I'm editing Matlab using augroup lang_matlab. What do I change to make this work?

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  • Classification: Dealing with Abstain/Rejected Class

    - by abner.ayala
    I am asking for your input and/help on a classification problem. If anyone have any references that I can read to help me solve my problem even better. I have a classification problem of four discrete and very well separated classes. However my input is continuous and has a high frequency (50Hz), since its a real-time problem. The circles represent the clusters of the classes, the blue line the decision boundary and Class 5 equals the (neutral/resting do nothing class). This class is the rejected class. However the problem is that when I move from one class to the other I activate a lot of false positives in the transition movements, since the movement is clearly non-linear. For example, every time I move from class 5 (neutral class) to 1 I first see a lot of 3's before getting to the 1 class. Ideally, I will want my decision boundary to look like the one in the picture below where the rejected class is Class =5. Has a higher decision boundary than the others classes to avoid misclassification during transition. I am currently implementing my algorithm in Matlab using naive bayes, kNN, and SVMs optimized algorithms using Matlab. Question: What is the best/common way to handle abstain/rejected classes classes? Should I use (fuzzy logic, loss function, should I include resting cluster in the training)?

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  • Use a vector to index a matrix without linear index

    - by David_G
    G'day, I'm trying to find a way to use a vector of [x,y] points to index from a large matrix in MATLAB. Usually, I would convert the subscript points to the linear index of the matrix.(for eg. Use a vector as an index to a matrix in MATLab) However, the matrix is 4-dimensional, and I want to take all of the elements of the 3rd and 4th dimensions that have the same 1st and 2nd dimension. Let me hopefully demonstrate with an example: Matrix = nan(4,4,2,2); % where the dimensions are (x,y,depth,time) Matrix(1,2,:,:) = 999; % note that this value could change in depth (3rd dim) and time (4th time) Matrix(3,4,:,:) = 888; % note that this value could change in depth (3rd dim) and time (4th time) Matrix(4,4,:,:) = 124; Now, I want to be able to index with the subscripts (1,2) and (3,4), etc and return not only the 999 and 888 which exist in Matrix(:,:,1,1) but the contents which exist at Matrix(:,:,1,2),Matrix(:,:,2,1) and Matrix(:,:,2,2), and so on (IRL, the dimensions of Matrix might be more like size(Matrix) = (300 250 30 200) I don't want to use linear indices because I would like the results to be in a similar vector fashion. For example, I would like a result which is something like: ans(time=1) 999 888 124 999 888 124 ans(time=2) etc etc etc etc etc etc I'd also like to add that due to the size of the matrix I'm dealing with, speed is an issue here - thus why I'd like to use subscript indices to index to the data. I should also mention that (unlike this question: Accessing values using subscripts without using sub2ind) since I want all the information stored in the extra dimensions, 3 and 4, of the i and jth indices, I don't think that a slightly faster version of sub2ind still would not cut it..

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  • Calculating confidence intervals for a non-normal distribution

    - by Josiah
    Hi all, First, I should specify that my knowledge of statistics is fairly limited, so please forgive me if my question seems trivial or perhaps doesn't even make sense. I have data that doesn't appear to be normally distributed. Typically, when I plot confidence intervals, I would use the mean +- 2 standard deviations, but I don't think that is acceptible for a non-uniform distribution. My sample size is currently set to 1000 samples, which would seem like enough to determine if it was a normal distribution or not. I use Matlab for all my processing, so are there any functions in Matlab that would make it easy to calculate the confidence intervals (say 95%)? I know there are the 'quantile' and 'prctile' functions, but I'm not sure if that's what I need to use. The function 'mle' also returns confidence intervals for normally distributed data, although you can also supply your own pdf. Could I use ksdensity to create a pdf for my data, then feed that pdf into the mle function to give me confidence intervals? Also, how would I go about determining if my data is normally distributed. I mean I can currently tell just by looking at the histogram or pdf from ksdensity, but is there a way to quantitatively measure it? Thanks!

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  • The use of getters and setters for different programming languages [closed]

    - by leonhart88
    So I know there are a lot of questions on getters and setters in general, but I couldn't find something exactly like my question. I was wondering if people change the use of get/set depending on different languages. I started learning with C++ and was taught to use getters and setters. This is what I understand: In C++ (and Java?), a variable can either be public or private, but we cannot have a mix. For example, I can't have a read-only variable that can still be changed inside the class. It's either all public (can read and change it), or all private (can't read and can only change inside the class). Because of this (and possibly other reasons), we use getters and setters. In MATLAB, I can control the "setaccess" and "getaccess" properties of variables, so that I can make things read-only (can directly access the property, but can't overwrite it). In this case, I don't feel like I need a getter because I can just do class.property. Also, in Python it is considered "Pythonic" to not use getters/setters and to only put things into properties if needed. I don't really understand why its OK to have all public variables in Python, because that's opposite of what I learned when I started with C++. I'm just curious what other people's thoughts are on this. Would you use getters and setters for all languages? Would you only use it for C++/Java and do direct access in MATLAB and Python (which is what I am currently doing)? Is the second option considered bad? For my purposes, I am only referring to simple getters and setters (just return/set the value and do not do anything else). Thanks!

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  • Get last row of many matrices (ASCII text files) and create a new matrix from these rows

    - by nofunsally
    I have over a thousand matrices (6 x 2000, ASCII files, comma delimited) that I generated from MATLAB. I want to get the last row of each matrix / text file and save them in a new matrix / text file. The text files have crazy names so when I load them I can name them whatever. Right now I would do this to achieve my goal: % A = load('crazyname.txt'); % B = load('crazynameagain.txt'); % C = load('crazynameyetagain.txt'); A = [5 5 5; 5 5 5; 1 1 1]; B = [5 5 5; 5 5 5; 2 2 2]; C = [5 5 5; 5 5 5; 3 3 3]; D(1,:)=A(end,:); D(2,:)=B(end,:); D(3,:)=C(end,:); I will create each command (e.g. load, building D step by step) in Excel by combining text cells to create a command. Is there a better way to do this? Could I load / assign the matrices with a name that would better suit them to be used in a for loop? Or is some other MATLAB command that would facilitate this? Thanks.

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  • Local Histogram Equalization with Matlab

    - by Mertie Pertie
    hi all Histogram equalization is simple with histeq function but when it comes local hist. eq., im supposed to use a neighbourhood and move it along the image matrix and do it locally at each iteration. I wonder how I can implement it with Matlab, is it possible if i use histeq for each neighbourhood or is there any other predefined m-function for this operation.

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  • Neural Net Optimize w/ Genetic Algorithm

    - by ServAce85
    Is a genetic algorithm the most efficient way to optimize the number of hidden nodes and the amount of training done on an artificial neural network? I am coding neural networks using the NNToolbox in Matlab. I am open to any other suggestions of optimization techniques, but I'm most familiar with GA's.

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  • Basic image processing question

    - by indoman
    Can you enlarge a feature so that rather than take up a certain number of pixels it actually takes up one or two times that many to make it easier to analyze? Would there be a way to generalize that in MATLAB?

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