747 research outputs found
Combined local search strategy for learning in networks of binary synapses
Learning in networks of binary synapses is known to be an NP-complete
problem. A combined stochastic local search strategy in the synaptic weight
space is constructed to further improve the learning performance of a single
random walker. We apply two correlated random walkers guided by their Hamming
distance and associated energy costs (the number of unlearned patterns) to
learn a same large set of patterns. Each walker first learns a small part of
the whole pattern set (partially different for both walkers but with the same
amount of patterns) and then both walkers explore their respective weight
spaces cooperatively to find a solution to classify the whole pattern set
correctly. The desired solutions locate at the common parts of weight spaces
explored by these two walkers. The efficiency of this combined strategy is
supported by our extensive numerical simulations and the typical Hamming
distance as well as energy cost is estimated by an annealed computation.Comment: 7 pages, 4 figures, figures and references adde
Improved Laguerre Spectral Methods with Less Round-off Errors and Better Stability
Laguerre polynomials are orthogonal polynomials defined on positive half line
with respect to weight . They have wide applications in scientific and
engineering computations. However, the exponential growth of Laguerre
polynomials of high degree makes it hard to apply them to complicated systems
that need to use large numbers of Laguerre bases. In this paper, we introduce
modified three-term recurrence formula to reduce the round-off error and to
avoid overflow and underflow issues in generating generalized Laguerre
polynomials and Laguerre functions. We apply the improved Laguerre methods to
solve an elliptic equation defined on the half line. More than one thousand
Laguerre bases are used in this application and meanwhile accuracy close to
machine precision is achieved. The optimal scaling factor of Laguerre methods
are studied and found to be independent of number of quadrature points in two
cases that Laguerre methods have better convergence speeds than mapped Jacobi
methods.Comment: 19pages, 8 figure
THE PO RIVER DELTA (ITALY) AND THE YELLOW RIVER DELTA (CHINA): THE STUDY AREA OF THE PROJECT
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Counting solutions from finite samplings
We formulate the solution counting problem within the framework of inverse
Ising problem and use fast belief propagation equations to estimate the entropy
whose value provides an estimate on the true one. We test this idea on both
diluted models (random 2-SAT and 3-SAT problems) and fully-connected model
(binary perceptron), and show that when the constraint density is small, this
estimate can be very close to the true value. The information stored by the
salamander retina under the natural movie stimuli can also be estimated and our
result is consistent with that obtained by Monte Carlo method. Of particular
significance is sizes of other metastable states for this real neuronal network
are predicted.Comment: 9 pages, 4 figures and 1 table, further discussions adde
On-site vibration test and dynamic response analysis of wind turbine of intertidal zone
In our study, the vibration signal of impulse response and attenuation response are extracted using the correlation function and power spectrum, and the natural frequency of wind turbine is determined. Compared with the rotation frequency of the blades of wind turbine which are 1p (one blade) and 3p (three blades), and wind vibration performance of the wind turbine is determined. The natural frequency of wind turbine is between the frequencies of one blade and three blades of wind turbine, which can avoid resonance phenomenon and meet the precision requirement for engineering application. The laws of acceleration and strain response along the wind turbine under ordinary wind load are obtained by installing acceleration sensor and strain gauge along the wind turbine. We found that the acceleration at the wind turbine top increases 10Â times than that at the bottom. The acceleration influenced by tide is 1.14 times than that with no tide. The strain produced maximum value at the opening place of wind turbine and near the top, it should be paid attention in the engineering design
Amplitude and Phase Statistics of Multi-look SAR Complex Interferogram
Amplitude and phase statistics of SAR complex interferogram are significant in the study of interferometry and polarimetry. To reduce statistical variations, multi-look processing is adopted by averaging spatially the complex interferogram. In this study, we derive and validate three kinds of probability density functions (PDFs) of multi-look interferogram for different surface feature scenes. For simple homogeneous areas with the gamma distribution intensity, a concise product-form interferometry phase PDF is derived, which is equivalent to a conventional Gauss hypergeometric PDF. For complicated areas with the K and G0 distributions intensity, two new interferometry amplitude PDFs named as Gamma-K and Gamma-G are proposed, and their phase PDFs are approximately preserved. Finally three typical areas including grass, mountain, and city are picked out from a pair of RADARSAT-2 SAR images and studied. Experimental results indicate good agreement between the computed histograms and the theoretical distributions. The results obtained can be applied to the feature classification of polarisation SAR data and the estimation of decorrelation effect of interferometric SAR.Science Journal, Vol. 64, No. 6, November 2014, pp.564-570, DOI:http://dx.doi.org/10.14429/dsj.64.474
Distributed optimization for multi-agent systems with communication delays and external disturbances under a directed network
This article studies the distributed optimization problem for multi-agent systems with communication delays and external disturbances in a directed network. Firstly, a distributed optimization algorithm is proposed based on the internal model principle in which the internal model term can effectively compensate for external environmental disturbances. Secondly, the relationship between the optimal solution and the equilibrium point of the system is discussed through the properties of the Laplacian matrix and graph theory. Some sufficient conditions are derived by using the Lyapunov–Razumikhin theory, which ensures all agents asymptotically reach the optimal value of the distributed optimization problem. Moreover, an aperiodic sampled-data control protocol is proposed, which can be well transformed into the proposed time-varying delay protocol and analyzed by using the Lyapunov–Razumikhin theory. Finally, an example is given to verify the effectiveness of the results
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