Support vector data description is applied as the subspace monitoring method. The availability of SASSVDD is verified through the fed-batch penicillin fermentationZhaomin LvXuefeng YanQingchao JiangChemometrics and Intelligent Laboratory SystemsLV Z M, YAN X F, JIANG Q C, et al. Batch process ...
Note that the Graph Laplacian regularization is based on the assumption that the representation coefficient vector corresponding to each sample, that is, C(:,i) for each i=1,…,n, is changing smoothly on each manifold [71]. Hence, nearby data points in the ambient space have similar ...
Independent component analysis-based non-Gaussian process monitoring with preselecting optimal components and support vector data description Independent component analysis (ICA)-based process monitoring methods have rapidly progressed, but independent components (ICs) selection remains an open q... Q Jiang...
Package descriptionjax-sysid is a Python package based on JAX for linear and nonlinear system identification of state-space models, recurrent neural network (RNN) training, and nonlinear regression/classification. The algorithm can handle L1-regularization and group-Lasso regularization and relies on L...
Based on the brief description about error propagation in the network, it is easy to see that the key factor is to reduce the number of propagated error. That is to say we should make the valuet' as small as possible. In (T−1 ⋅ TZ → Y) ⋅ Z, Z is objective...
2 Problem Description and Our Solution Consider K groups data points X = [X1, X2, ··· , XK ] and assume that there are n1, n2, ··· , nK data points in each group, respectively ( K k=1 nk = n). We assume that for each group, the data points belong to independent ...
For discrete-time models, the software sets'Ts'to the sample time of the data in the units stored in theTimeUnitproperty. 0(default) |scalar|vector Input delay for each input channel, specified as the comma-separated pair consisting of'InputDelay'and a numeric vector. ...
To address the abovementioned issues, an improved batch process monitoring approach is presented that integrates just‐in‐time learning and multiple subspace support vector data description (JITL‐MSSVDD). A new multiple subspace segmentation method is proposed that classifies a contribution array that ...
Feature learningTexture structure dictionaryBinary label relaxation modelShared weights support vector data descriptionPattern recognitionTo address the problem of face recognition where the number of the labeled samples is insufficient and those samples involve pose, illumination and expression variations, etc...
To address the abovementioned issues, an improved batch process monitoring approach is presented that integrates just-in-time learning and multiple subspace support vector data description (JITL-MSSVDD). A new multiple subspace segmentation method is proposed that classifies a contribution array that is...