35,247 research outputs found

    On the permanent of random Bernoulli matrices

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    We show that the permanent of an n×nn \times n matrix with iid Bernoulli entries ±1\pm 1 is of magnitude n(1/2+o(1))nn^{({1/2}+o(1))n} with probability 1o(1)1-o(1). In particular, it is almost surely non-zero

    A short proof of Kneser's addition theorem for abelian groups

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    Martin Kneser proved the following addition theorem for every abelian group GG. If A,BGA,B \subseteq G are finite and nonempty, then A+BA+K+B+KK|A+B| \ge |A+K| + |B+K| - |K| where K={gGg+A+B=A+B}K = \{g \in G \mid g+A+B = A+B \}. Here we give a short proof of this based on a simple intersection union argument.Comment: 3 page

    A Pulse-Gated, Predictive Neural Circuit

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    Recent evidence suggests that neural information is encoded in packets and may be flexibly routed from region to region. We have hypothesized that neural circuits are split into sub-circuits where one sub-circuit controls information propagation via pulse gating and a second sub-circuit processes graded information under the control of the first sub-circuit. Using an explicit pulse-gating mechanism, we have been able to show how information may be processed by such pulse-controlled circuits and also how, by allowing the information processing circuit to interact with the gating circuit, decisions can be made. Here, we demonstrate how Hebbian plasticity may be used to supplement our pulse-gated information processing framework by implementing a machine learning algorithm. The resulting neural circuit has a number of structures that are similar to biological neural systems, including a layered structure and information propagation driven by oscillatory gating with a complex frequency spectrum.Comment: This invited paper was presented at the 50th Asilomar Conference on Signals, Systems and Computer

    Moderate deviations for the determinant of Wigner matrices

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    We establish a moderate deviations principle (MDP) for the log-determinant logdet(Mn)\log | \det (M_n) | of a Wigner matrix MnM_n matching four moments with either the GUE or GOE ensemble. Further we establish Cram\'er--type moderate deviations and Berry-Esseen bounds for the log-determinant for the GUE and GOE ensembles as well as for non-symmetric and non-Hermitian Gaussian random matrices (Ginibre ensembles), respectively.Comment: 20 pages, one missing reference added; Limit Theorems in Probability, Statistics and Number Theory, Springer Proceedings in Mathematics and Statistics, 201

    Graded, Dynamically Routable Information Processing with Synfire-Gated Synfire Chains

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    Coherent neural spiking and local field potentials are believed to be signatures of the binding and transfer of information in the brain. Coherent activity has now been measured experimentally in many regions of mammalian cortex. Synfire chains are one of the main theoretical constructs that have been appealed to to describe coherent spiking phenomena. However, for some time, it has been known that synchronous activity in feedforward networks asymptotically either approaches an attractor with fixed waveform and amplitude, or fails to propagate. This has limited their ability to explain graded neuronal responses. Recently, we have shown that pulse-gated synfire chains are capable of propagating graded information coded in mean population current or firing rate amplitudes. In particular, we showed that it is possible to use one synfire chain to provide gating pulses and a second, pulse-gated synfire chain to propagate graded information. We called these circuits synfire-gated synfire chains (SGSCs). Here, we present SGSCs in which graded information can rapidly cascade through a neural circuit, and show a correspondence between this type of transfer and a mean-field model in which gating pulses overlap in time. We show that SGSCs are robust in the presence of variability in population size, pulse timing and synaptic strength. Finally, we demonstrate the computational capabilities of SGSC-based information coding by implementing a self-contained, spike-based, modular neural circuit that is triggered by, then reads in streaming input, processes the input, then makes a decision based on the processed information and shuts itself down

    A note on local well-posedness of generalized KdV type equations with dissipative perturbations

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    In this note we report local well-posedness results for the Cauchy problems associated to generalized KdV type equations with dissipative perturbation for given data in the low regularity L2L^2-based Sobolev spaces. The method of proof is based on the {\em contraction mapping principle} employed in some appropriate time weighted spaces.Comment: 14 page

    Small ball probability, Inverse theorems, and applications

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    Let ξ\xi be a real random variable with mean zero and variance one and A=a1,...,anA={a_1,...,a_n} be a multi-set in Rd\R^d. The random sum SA:=a1ξ1+...+anξnS_A := a_1 \xi_1 + ... + a_n \xi_n where ξi\xi_i are iid copies of ξ\xi is of fundamental importance in probability and its applications. We discuss the small ball problem, the aim of which is to estimate the maximum probability that SAS_A belongs to a ball with given small radius, following the discovery made by Littlewood-Offord and Erdos almost 70 years ago. We will mainly focus on recent developments that characterize the structure of those sets AA where the small ball probability is relatively large. Applications of these results include full solutions or significant progresses of many open problems in different areas.Comment: 47 page
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