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A methodology to analyze device-to-circuit characteristics and predict memory array performance is presented. With a five- parameter characterization of the selection device and a compact model of RRAM, we are able to capture the behaviors of reported selection devices and simulate 1S1R cell/array performance with RRAM compact modeling using HSPICE. To predict the performance of the memory array for...
Coupling graphs are newly introduced in this paper to meet many application needs particularly in the field of bioinformatics. A coupling graph is a two-layer graph complex, in which each node from one layer of the graph complex has at least one connection with the nodes in the other layer, and vice versa. The coupling graph model is sufficiently powerful to capture strong and inherent associations...
Differently from traditional machine learning techniques applied to data classification, high level classification considers not only the physical features of the data (distance, similarity or distribution), but also the pattern formation of the data. In this latter case, a set of complex network measures are employed because of their abilities to capture spatial, functional and topological relations...
As the next generation standard of video coding, the High Efficiency Video Coding (HEVC) is intended to provide significantly better coding efficiency than all existing video coding standards. To improve the coding efficiency of intra frame coding, up to 34 intra prediction modes are defined in HEVC. The best mode among these pre-defined intra prediction modes is selected by rate-distortion optimization...
This paper presents TSK interval type-2 fuzzy neural network (TSK IT2FNN)and its learning algorithm for chaotic time series prediction. First, The structure of TSK IT2FNN is decided using the hierarchical fuzzy clustering algorithm. Then its parameters of the precondition membership function and consequence weight are optimized using the gradient descent algorithm. Finally the effectiveness of IT2FNN...
The paper proposed an algorithm which can get over the BP algorithm's shortcomings of slow convergence speed, computation complexity and local minimum by using the UKF to estimate the parameters of WNN. Then it takes the phenomenon of aerodynamic modeling of quasi-steady stall for ATTAS aircraft as applying background and uses the algorithm of BP, EKF and UKF to train the WNN respectively. From the...
This paper proposes a novel technique that combines orthogonal least-squares (OLS) and culture algorithm (CA) to construct the radial basis function (RBF) network for the wind power forecast. By reason of the fluctuation and volatility in wind, wind power generations provide a challenge to the security and stability of the electric system, thus the growing revolution in wind energy encourages more...
The growing revolution in wind energy encourages more accurate models for wind speed forecasting as the wind is fluctuate, periodic and volatile. An artificial neural network (ANN) method is used to predict the average hourly wind speed. Different from the multilayer perception network (MLP) which is more conversant, this paper presents a novel technique based on radial basis function (RBF) network...
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