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Publikováno v:
IJCNN
Least square support vector machines (LSSVMs) are an alternative to SVMs because the training process for LSSVMs is based on solving a linear equation system while the training process for SVMs relies on solving a quadratic programming optimization p
Publikováno v:
IJCNN
D-Wave 2X with more than 1000 qubits was applied to the relatively rugged energy landscape of trained Restricted Boltzmann Machines (RBMs). The D-Wave machine has a Chimera interconnect architecture. A native RBM restricted to the Chimera graph was f
Publikováno v:
IJCNN
Spiking neuron models, which can realize diverse kinds of neural coding by describing spiking activity of membrane potential, have been widely utilized. Among these models, several hybrid spiking neuron models, which combine continuous spike-generati
Autor:
Shayan Garani Srinivasa, Prayag Gowgi
Publikováno v:
IJCNN
We look at the neural network as a non-linear probability density function (pdf) transformer by stochastic learning cumulative (SLC) technique. We formulate a potential function that drives a neural network to non-linearly transform the input pdf to
Publikováno v:
IJCNN
An adaptive target scheme is implemented for learning control of population transfer between subspaces of quantum systems. In this control scheme, the target state is updated according to the renormalized yield in the desired subspace throughout the
Publikováno v:
IJCNN
Kernel k-means is seen as a non-linear extension of the k-means clustering method, with good performance in identifying non-isotropic and linearly inseparable clusters. However space and time requirement of kernel k-means is expensive with O(n2) comp
Autor:
Mark D. McDonnell, Philip de Chazal
Publikováno v:
IJCNN
An efficient algorithm for the calculation of the approximate Hessian matrix for the Levenberg-Marquardt (LM) optimization algorithm for training a single-hidden-layer feed forward network with linear outputs is presented. The algorithm avoids explic
Publikováno v:
IJCNN
Kernel independent component analysis (KICA) has an important application in blind source separation, in which how to select the optimal kernel, including the kernel functional form and its parameters, is the key issue for obtaining the optimal perfo
Publikováno v:
IJCNN
A wavelet neural network (WNN)-based robust total-sliding-mode control scheme is developed for the synchronization of uncertain chaotic systems. The proposed control system offers a design method to drive the state trajectory to track a desired traje
Publikováno v:
IJCNN
We propose a conjugate descent procedure for the second order SMO algorithm that leads to a substantial decrease in the number of iterations required for SMO to converge to a given precision with a modest increase in the iteration cost.