{"id":1925,"date":"2022-08-30T15:20:35","date_gmt":"2022-08-30T15:20:35","guid":{"rendered":"https:\/\/unknownerror.org\/index.php\/2013\/12\/02\/problem-about-neural-network-collection-of-common-programming-errors\/"},"modified":"2022-08-30T15:20:35","modified_gmt":"2022-08-30T15:20:35","slug":"problem-about-neural-network-collection-of-common-programming-errors","status":"publish","type":"post","link":"https:\/\/unknownerror.org\/index.php\/2022\/08\/30\/problem-about-neural-network-collection-of-common-programming-errors\/","title":{"rendered":"problem about neural-network-Collection of common programming errors"},"content":{"rendered":"<ul>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/ecd3330e754bea4311cb61844cff505c?s=32&amp;d=identicon&amp;r=PG&amp;f=1\" \/><br \/>\ndammikasandaruwan<br \/>\nvisual-studio-2010 visual-c++ neural-network fann<br \/>\ni am new to the c++ working environment and these days i am working in a neural network project. so i decided to use FANN neural network library. i create my own c++ win 32 solution and add all the relavant files from FANN downloaded source folder. then i run the xor sample example which is in FANN 2.2\/vs2010 folder. but when i run the project it generates unhandled exception called Unhandled exception at 0x77ea15ee in test7.exe: 0xC0000005: Access violation writing location 0x003a6010.in the de<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/i.stack.imgur.com\/9tHn8.jpg?s=32&amp;g=1\" \/><br \/>\nshridatt<br \/>\nandroid neural-network noclassdeffounderror<br \/>\nI am using neuroPh 2.7 for my android app. When i tried to load the neural network i get the following error. The stacktrace is as follows06-01 12:50:14.353: W\/dalvikvm(2780): VFY: unable to resolve static method 4482: Lorg\/neuroph\/core\/NeuralNetwork;.load (Ljava\/io\/InputStream;)Lorg\/neuroph\/core\/NeuralNetwork; 06-01 12:50:14.353: W\/dalvikvm(2780): VFY: unable to resolve virtual method 4483: Lorg\/neuroph\/core\/NeuralNetwork;.setInput ([D)V 06-01 12:50:14.363: W\/dalvikvm(2780): VFY: unable to reso<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/f0aeac35a15cbe0c875552b4ccbe7eeb?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nDavid Williams<br \/>\npython neural-network swig fann<br \/>\nI just built and installed libfann and the associated python bindings. The python setup seemed to run ok:$ sudo python setup.py install Running SWIG before: swig -c++ -python pyfann\/pyfann.i running install running build running build_py copying pyfann\/libfann.py -&gt; build\/lib.macosx-10.5-x86_64-2.7\/pyfann running build_ext building &#8216;pyfann._libfann&#8217; extension gcc -fno-strict-aliasing -I\/Users\/dwilliams\/Desktop\/Anaconda\/include -arch x86_64 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -D<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/1b4d1c6bf38e484f66faa12dc9725f49?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nSmi<br \/>\nmatlab neural-network sim-card<br \/>\nMy project is to recognize ancient coins. I am using Matlab. I already have a feature file which contains both inputs and output. I have trained 3 types of coins using newff and net had been saved. For the three types of coins, I used 01, 10 and 11 as targets. Now I want to use that trained net for testing. I have test images too. I coded like this:load net.mat; load features.mat; testInputs = Features&#8217;; out = sim(net,testInputs); [dummy, I]=max(out);Value of I is using to check the coin type. I<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/i.stack.imgur.com\/Z99mk.jpg?s=32&amp;g=1\" \/><br \/>\nFranck Dernoncourt<br \/>\nmatlab neural-network matlab-toolbox<br \/>\nIn MATLAB, feedforwardnet(8) creates a feedforward network with one hidden layer containing 8 hidden neurons. MATLAB stores numeric data as double-precision floating point (double) by default. Therefore feedforwardnet(8) is equivalent to feedforwardnet(double(8)). However, feedforwardnet(int32(8)) will raise the following error:Undefined function or variable &#8216;ind&#8217;.Error in network\/subsasgn&gt;setLayerSize (line 1170)err = sprintf(&#8216;&#8221;layers{%g}.size&#8221; must be a positive integer.&#8217;,ind);Error in netw<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/16e642660bb8cef73ca10fc35069c678?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nMHardy<br \/>\nartificial-intelligence neural-network ubuntu-12.04 fann<br \/>\nI am trying to build fann neural network library in ubuntu 12.04 but failed to use it as the testing routine is not working. Following the instructions in http:\/\/leenissen.dk\/fann\/wp\/help\/installing-fann\/. After cmake and install when I want to test if the library is working, by cd to examples and then running:make runtestwhat I get is here:gcc -O3 xor_train.c -o xor_train -lfann -lm gcc -O3 xor_test.c -o xor_test -lfann -lm gcc -O3 -DFIXEDFANN xor_test.c -o xor_test_fixed -lfixedfann -lm gcc -O<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/6b16d1e14414d995cf2b8c760bb97b88?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nTrung Huynh<br \/>\npython artificial-intelligence neural-network time-series<br \/>\nI want to use neural networks to predict a timeseries B in the next 30 days from now based on a series A (I have the full history of series A), and a list of events E in the next 30 days (E is a list of binary units). Knowing that B is linearly proportional to A and when an event in day i happens (E[i] = 1), it triggers a spike on B (the ratio is unknown). I have training data containing tuples of (A, E, B). I have tested with feed forward network, but it doesn&#8217;t perform very well (not predictin<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/beb61223e8f7b42692772a80eda0eb71?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nuser1068446<br \/>\nmachine-learning neural-network weka xor<br \/>\nI&#8217;m just getting started with Weka and having trouble with the first steps.We&#8217;ve got our training set:@relation PerceptronXOR @attribute X1 numeric @attribute X2 numeric @attribute Output numeric @data 1,1,-1 -1,1,1 1,-1,1 -1,-1,-1First step I want to do is just train, and then classify a set using the Weka gui. What I&#8217;ve been doing so far:Using Weka 3.7.0.Start GUI. Explorer. Open file -&gt; choose my arff file. Classify tab. Use training set radio button. Choose-&gt; functions&gt;multilayer_perceptr<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/57b20c8b9929880e3f077705e575a362?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nmuntoo<br \/>\njava matlab neural-network<br \/>\nI&#8217;m working on my final year project. I need to load Matlab neural network from Java.This is the method I have created to load the neural network:function [result] = viewforecasteddata(newinputs)%#function network load(&#8216;Test.mat&#8217;,&#8217;net&#8217;);result = net(newinputs);endThis how I&#8217;m calling from Java:result = theCost.viewforecasteddata(1,mWNumericArray);I&#8217;m getting these warnings and exceptions:{Warning: While loading an object of class &#8216;nnetWeight&#8217;: Undefined function or method &#8216;initzero&#8217; for input a<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/5eda56a779ba5f1e295d48fd1e341cca?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nMrLinjak<br \/>\nvisual-studio-2010 neural-network neural-network-tuning fann<br \/>\nBefore I ask my question, here&#8217;s a brief summary of my project:I&#8217;m using OPENCV&#8217;s built-in function to detect a face in a cam-feed. After that I&#8217;m processing the image which contains the face, i.e. converting it to grayscale, resizing it to 40X40 pixels and equalizing its&#8217; histogram. The pixel values of the image are then read, normalized (i.e. divided by 256 since FANN works with values between 0 and 1, or -1 and 1, depending on the used function) and saved into an array of 1600 elements. This<\/li>\n<li>\n<img decoding=\"async\" src=\"http:\/\/www.gravatar.com\/avatar\/d6d19d6f112fd516053145e3c3ac1528?s=32&amp;d=identicon&amp;r=PG\" \/><br \/>\nSahar<br \/>\nmatlab neural-network outofmemoryerror<br \/>\nI have a problem which occurs when I write the command line of the rbf (radial basis function) neural networknet = newrb(T, D);I get the error **??? Error using ==&gt; unknown Out of memory. Type HELP MEMORY for your options.Error in ==&gt; dist&gt;apply at 119 z = zeros(S,Q);Error in ==&gt; boiler_weight at 38 result = apply(a,b,c);Error in ==&gt; dist at 90 boiler_weightError in ==&gt; newrb&gt;designrb at 143 P = radbas(dist(p&#8217;,p)*b);Error in ==&gt; newrb at 127 [w1,b1,w2,b2,tr] = designrb(p,<\/li>\n<\/ul>\n<p id=\"rop\"><small>Originally posted 2013-12-02 21:21:56. <\/small><\/p>","protected":false},"excerpt":{"rendered":"<p>dammikasandaruwan visual-studio-2010 visual-c++ neural-network fann i am new to the c++ working environment and these days i am working in a neural network project. so i decided to use FANN neural network library. i create my own c++ win 32 solution and add all the relavant files from FANN downloaded source folder. then i run [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1925","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/posts\/1925","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/comments?post=1925"}],"version-history":[{"count":0,"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/posts\/1925\/revisions"}],"wp:attachment":[{"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/media?parent=1925"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/categories?post=1925"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/unknownerror.org\/index.php\/wp-json\/wp\/v2\/tags?post=1925"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}