这些操作在此示例末尾的帮助函数imageRegressionAugmentationPipeline中定义。使用transform函数将数据增强应用于训练数据。 dsTrain=transform(dsCombined,@imageRegressionAugmentationPipeline);montage(preview(dsTrain)',Size=[62])title("CombinedI
How to transform Matlab function to s-function. Learn more about s-function MATLAB and Simulink Student Suite
Find the Fourier transform of the cosine function. Get f = a*cos(b*t); FT = fourier(f) FT = π a (δ(b+w)+δ(b−w)) Find the Fourier transform of the sine function. Get f = a*sin(b*t); FT = fourier(f) ...
扩充和预处理训练数据,是使用transform函数,并带有辅助函数augmentDataForDayToDusk指定的自定义预处理操作来完成的。此函数作为支持文件附加到示例中。 augmentDataForDayToDusk函数执行以下操作: 使用双三次插值将图像调整为指定的输入大小。 在水平方向随机翻转图像。 将图像缩放到范围 [-1, 1]。该范围与生成器中使...
Function that transforms the data, specified as a function handle. The function takes data as an input and returns the transformed data, based on the transformations defined infcn. The transform function must have this signature andds1_data,ds2_data,...dsN_datamust be of the same form as th...
Set this value to "acrosscolumns" if you want the time dimension of s across the columns and the frequency dimension down the rows. This input is ignored if the function is called without output arguments.Output Arguments collapse all s— Short-time Fourier transform matrix | 3-D array ...
This MATLAB function computes the discrete Fourier transform (DFT) of X using a fast Fourier transform (FFT) algorithm.
The transfer function is the Z-transform of the system’s impulse response. It can be expressed in terms of the state-space matrices as H(z)=C(zI−A)−1B+D. For continuous-time systems, the state-space matrices relate the state vectorx, the inputu, and the outputythrough ...
other%trnasforms, so let the logTransform function handle that and then%return.g=logTransform(f,varargin(:));return;end%if f is floating point, check to see if it is in the range [0 1].%If it is not, force it to be using function mat2gray.ifisfloat(f) && (max(f(:))>1||...
function testloss = myloss(TrainTbl,trainY,TestTbl,testY) [Transformer,NewTrainTbl] = genrfeatures(TrainTbl,trainY,20); NewTestTbl = transform(Transformer,TestTbl); Mdl = fitrlinear(NewTrainTbl,trainY); testloss = loss(Mdl,NewTestTbl,testY); end Train Model Using Subset of Generated Feat...