forward orthogonal least-squares algorithm
Finite impulse response filter design using a forward orthogonal least squares algorithm
... There are many well developed FIR filter design methods. The fir2() routine is one method embedded in the MAT- LAB signal processing toolbox, which can be used to design frequency sampling-based FIR filters with ...
7
Regularized orthogonal least squares algorithm for constructing radial basis function networks
... The proposed algorithm combines the advantages of both the orthogonal forward regression and regularization methods to provide an efficient and powerful procedure for constructing parsim[r] ...
10
Parsimonious least squares support vector regression using orthogonal forward selection with the generalised kernel model
... construction algorithm, called the LS-SESVM, has been ...OLS forward selection procedure and the corresponding model weights are then computed using the LS-ESVM ...SVM algorithm but it is able to ...
12
Orthogonal least squares regression with tunable kernels
... proposed algorithm tunes the centre vector and diagonal covariance matrix of individual regressor by incrementally minimising the training mean square error (MSE) in an orthogonal forward selection ...
5
An Orthogonal Forward Regression Algorithm Combined with Basis Pursuit and D Optimality
... new forward regression model identification algorithm is ...each forward regression step, are initially estimated via orthogonal least squares (OLS) (using the modified ...
6
Sparse model identification using orthogonal forward regression with basis pursuit and D optimality
... identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and ...each forward regression step are ...
8
Joint k-step analysis of Orthogonal Matching Pursuit and Orthogonal Least Squares
... as forward selection in statistical regression [7] and as the greedy algorithm [5], Order Recursive Matching Pursuit (ORMP) [8] and Optimized Orthogonal Matching Pursuit (OOMP) [9] in the signal ...
21
Identification of nonlinear systems with non-persistent excitation using an iterative forward orthogonal least squares regression algorithm
... OFR algorithm may include redundant autoregressive terms, even when the data set was produced from a purely moving average model (Piroddi and Spinelli, ...iOFR algorithm can correctly identify an optimal ...
14
Sparse kernel regression modelling using combined locally regularized orthogonal least squares and D optimality experimental design
... LROLS algorithm, the choice of is less critical than the original OLS ...in forward regression only affects the stopping point of the model selection, but does not penalizes the regressor that may cause ...
8
Ultra-Orthogonal Forward Regression Algorithms for the Identification of Non-Linear Dynamic Systems
... Ultra Least Squares (ULS) criterion is introduced for system ...standard least squares criterion which is based on the Euclidean norm of the residuals, the new ULS criterion is derived from ...
25
An iterative orthogonal forward regression algorithm
... associated Orthogonal Forward Regression (OFR) algorithm have been widely applied in nonlinear system identification including in the modelling of many engineering, chemical, biological, medical, ...
28
A modified orthogonal forward regression least-squares algorithm for system modelling from noisy regressors
... Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the rea[r] ...
21
A Robust Collaborative Recommendation Algorithm Based on Least Median Squares Estimator
... LMedSMF algorithm, we also conduct experiments on the MovieLens 10M dataset and compare LMedSMF with MMF and LTSMF in terms of accuracy and prediction shift ...
7
Least Squares Matrix Algorithm for State Space Modelling of Dynamic Systems
... novel least squares matrix algorithm (LSM) for the analysis of rapidly changing systems using state-space ...LSM algorithm is based on the Hankel structured data matrix ...LSM algorithm ...
5
Object Detection and Tracking Using Uncalibrated Cameras
... The work presented in this thesis deals with the estimation of the 3D position of an object from stereo images. The problem is decomposed into a number of tasks, each task being associated with a specific geometric ...
68
Orthogonal Forward Regression based on Directly Maximizing Model Generalization Capability
... construction algorithm for sparse kernel modelling using the leave-one-out test score also known as the PRESS (Predicted REsidual Sums of Squares) ...the orthogonal forward regression ...
6
Newton Krylov Type Algorithm for Solving Nonlinear Least Squares Problems
... The presented algorithm is a Newton-Krylov type algorithm. It requires a fixed-size limited storage proportional to the size of the problem and relies only upon matrix vector product. It is based on the ...
17
Recursive Least Squares Dictionary Learning Algorithm for Electrical Impedance Tomography
... EIT image is reconstructed based on the dictionary learning algorithm discussed in Section 2, and the conductivity distribution is obtained by measuring the changes in voltage. RLS-DLA is used to learn an initial ...
12
Rapid detection of total nitrogen content in soy sauce using NIR spectroscopy
... A method for the rapid and nondestructive determination of total nitrogen content in soy sauce was explored. Pre- diction models were established using near-infrared spectroscopy combined with each of the following ...
6
A general order multichannel, fast least squares algorithm with telecommunications applications
... It was derived using the recursive form of (2.6) and the matrix inversion lemma [52), which generates an explicit inverse formula for matrices of a certain type. The algorithm sequence i[r] ...
182