Results 271 to 280 of about 107,979 (335)
Confirming universality of the fractal dimension of incipient percolation cluster for complex neighborhoods. [PDF]
Sci RepMalarz K, Krawczyk MJ.
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Factor Graph-Based Online Bayesian Identification and Component Evaluation for Multivariate Autoregressive Exogenous Input Models. [PDF]
Entropy (Basel)Nisslbeck TN, Kouw WM.
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Deep kernel recursive least-squares algorithm
Nonlinear Dynamics, 2021We present a new kernel-based algorithm for modeling evenly distributed multidimensional datasets that does not rely on input space sparsification. The presented method reorganizes the typical single-layer kernel-based model into a deep hierarchical structure, such that the weights of a kernel model over each dimension are modeled over its adjacent ...
Hossein Mohamadipanah +2 more
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Quaternion kernel recursive least-squares algorithm
Signal Processing, 2021Abstract Various kernel-based algorithms have been successfully applied to nonlinear problems in adaptive filters over the last two decades. In this paper, we study a kernel recursive least squares (KRLS) algorithm in the quaternion domain. By the generalized Hamilton-real calculus method, we can apply the kernel trick to calculate the quaternion ...
Gang Wang +3 more
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Quantized Kernel Recursive Least Squares Algorithm
IEEE Transactions on Neural Networks and Learning Systems, 2013In a recent paper, we developed a novel quantized kernel least mean square algorithm, in which the input space is quantized (partitioned into smaller regions) and the network size is upper bounded by the quantization codebook size (number of the regions).
Badong, Chen +3 more
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Linearly-Constrained Recursive Total Least-Squares Algorithm
IEEE Signal Processing Letters, 2012We develop a new linearly-constrained recursive total least squares adaptive filtering algorithm by incorporating the linear constraints into the underlying total least squares problem using an approach similar to the method of weighting and searching for the solution (filter weights) along the input vector.
R. Arablouei, K. Dogancay
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Order-recursive underdetermined recursive least-squares adaptive algorithms
Signal Processing, 1997zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baykal, B., Constantinides, A. G.
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Recursive least squares ladder estimation algorithms
IEEE Transactions on Circuits and Systems, 1981Recursive least squares ladder estimation algorithms have attracted much attention recently because of their excellent convergence behavior and fast parameter tracking capability, compared to gradient based algorithms. We present some recently developed square root normalized exact least squares ladder form algorithms that have fewer storage ...
Lee, Daniel T. L. +2 more
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Splitting the recursive least-squares algorithm
Proceedings of the Sixth International Symposium on Signal Processing and its Applications (Cat.No.01EX467), 2002Exponentially weighted recursive least-squares (RLS) algorithms are commonly used for fast adaptation. In many cases the input signals are continuous-time. Then either a fully analog implementation of the RLS algorithm is applied or the input data are sampled by analog-to-digital (AD) converters to be processed digitally. Although a digital realization
T. Magesacher +5 more
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Recursive Least-Squares Algorithms
2011Thanks to their fast convergence rate, recursive least-squares (RLS) algorithms are very popular in SAEC [1]. Indeed, it is well known that the convergence rate of RLS-type algorithms are not much affected by the nature of the input signal, even when this one is ill-conditioned.
Jacob Benesty +3 more
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