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  • Bias/Variance Decompositions for Likelihood-Based Estimators.

    abstract::The bias/variance decomposition of mean-squared error is well understood and relatively straightforward. In this note, a similar simple decomposition is derived, valid for any kind of error measure that, when using the appropriate probability model, can be derived from a Kullback-Leibler divergence or log-likelihood. ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017232

    authors: Heskes T

    更新日期:1998-07-28 00:00:00

  • Pattern generation by two coupled time-discrete neural networks with synaptic depression.

    abstract::Numerous animal behaviors, such as locomotion in vertebrates, are produced by rhythmic contractions that alternate between two muscle groups. The neuronal networks generating such alternate rhythmic activity are generally thought to rely on pacemaker cells or well-designed circuits consisting of inhibitory and excitat...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017449

    authors: Senn W,Wannier T,Kleinle J,Lüscher HR,Müller L,Streit J,Wyler K

    更新日期:1998-07-01 00:00:00

  • Changes in GABAB modulation during a theta cycle may be analogous to the fall of temperature during annealing.

    abstract::Changes in GABA modulation may underlie experimentally observed changes in the strength of synaptic transmission at different phases of the theta rhythm (Wyble, Linster, & Hasselmo, 1997). Analysis demonstrates that these changes improve sequence disambiguation by a neural network model of CA3. We show that in the fra...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017539

    authors: Sohal VS,Hasselmo ME

    更新日期:1998-05-15 00:00:00

  • Toward a biophysically plausible bidirectional Hebbian rule.

    abstract::Although the commonly used quadratic Hebbian-anti-Hebbian rules lead to successful models of plasticity and learning, they are inconsistent with neurophysiology. Other rules, more physiologically plausible, fail to specify the biological mechanism of bidirectionality and the biological mechanism that prevents synapses...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017629

    authors: Grzywacz NM,Burgi PY

    更新日期:1998-04-01 00:00:00

  • Nonlinear Time&hyphenSeries Prediction with Missing and Noisy Data

    abstract::We derive solutions for the problem of missing and noisy data in nonlinear time&hyphenseries prediction from a probabilistic point of view. We discuss different approximations to the solutions &hyphen in particular, approximations that require either stochastic simulation or the substitution of a single estimate for t...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/089976698300017728

    authors: Tresp V V,Hofmann R

    更新日期:1998-03-23 00:00:00

  • Synaptic runaway in associative networks and the pathogenesis of schizophrenia.

    abstract::Synaptic runaway denotes the formation of erroneous synapses and premature functional decline accompanying activity-dependent learning in neural networks. This work studies synaptic runaway both analytically and numerically in binary-firing associative memory networks. It turns out that synaptic runaway is of fairly m...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/089976698300017836

    authors: Greenstein-Messica A,Ruppin E

    更新日期:1998-02-15 00:00:00

  • Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell.

    abstract::To understand the interspike interval (ISI) variability displayed by visual cortical neurons (Softky & Koch, 1993), it is critical to examine the dynamics of their neuronal integration, as well as the variability in their synaptic input current. Most previous models have focused on the latter factor. We match a simple...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1997.9.5.971

    authors: Troyer TW,Miller KD

    更新日期:1997-07-01 00:00:00

  • Similarity, connectionism, and the problem of representation in vision.

    abstract::A representational scheme under which the ranking between represented similarities is isomorphic to the ranking between the corresponding shape similarities can support perfectly correct shape classification because it preserves the clustering of shapes according to the natural kinds prevailing in the external world. ...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/neco.1997.9.4.701

    authors: Edelman S,Duvdevani-Bar S

    更新日期:1997-05-15 00:00:00

  • Conductance-based integrate-and-fire models.

    abstract::A conductance-based model of Na+ and K+ currents underlying action potential generation is introduced by simplifying the quantitative model of Hodgkin and Huxley (HH). If the time course of rate constants can be approximated by a pulse, HH equations can be solved analytically. Pulse-based (PB) models generate action p...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1997.9.3.503

    authors: Destexhe A

    更新日期:1997-04-01 00:00:00

  • Binocular receptive field models, disparity tuning, and characteristic disparity.

    abstract::Disparity tuning of visual cells in the brain depends on the structure of their binocular receptive fields (RFs). Freeman and coworkers have found that binocular RFs of a typical simple cell can be quantitatively described by two Gabor functions with the same gaussian envelope but different phase parameters in the sin...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1996.8.8.1611

    authors: Zhu YD,Qian N

    更新日期:1996-11-15 00:00:00

  • The dynamics of discrete-time computation, with application to recurrent neural networks and finite state machine extraction.

    abstract::Recurrent neural networks (RNNs) can learn to perform finite state computations. It is shown that an RNN performing a finite state computation must organize its state space to mimic the states in the minimal deterministic finite state machine that can perform that computation, and a precise description of the attracto...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1996.8.6.1135

    authors: Casey M

    更新日期:1996-08-15 00:00:00

  • Modeling slowly bursting neurons via calcium store and voltage-independent calcium current.

    abstract::Recent experiments indicate that the calcium store (e.g., endoplasmic reticulum) is involved in electrical bursting and [Ca2+]i oscillation in bursting neuronal cells. In this paper, we formulate a mathematical model for bursting neurons, which includes Ca2+ in the intracellular Ca2+ stores and a voltage-independent c...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1996.8.5.951

    authors: Chay TR

    更新日期:1996-07-01 00:00:00

  • Alignment of coexisting cortical maps in a motor control model.

    abstract::How do multiple feature maps that coexist in the same region of cerebral cortex align with each other? We hypothesize that such alignment is governed by temporal correlations: features in one map that are temporally correlated with those in another come to occupy the same spatial locations in cortex over time. To exam...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1996.8.4.731

    authors: Chen Y,Reggia JA

    更新日期:1996-05-15 00:00:00

  • Regularized neural networks: some convergence rate results.

    abstract::In a recent paper, Poggio and Girosi (1990) proposed a class of neural networks obtained from the theory of regularization. Regularized networks are capable of approximating arbitrarily well any continuous function on a compactum. In this paper we consider in detail the learning problem for the one-dimensional case. W...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1995.7.6.1225

    authors: Corradi V,White H

    更新日期:1995-11-01 00:00:00

  • Methods for combining experts' probability assessments.

    abstract::This article reviews statistical techniques for combining multiple probability distributions. The framework is that of a decision maker who consults several experts regarding some events. The experts express their opinions in the form of probability distributions. The decision maker must aggregate the experts' distrib...

    journal_title:Neural computation

    pub_type: 杂志文章,评审

    doi:10.1162/neco.1995.7.5.867

    authors: Jacobs RA

    更新日期:1995-09-01 00:00:00

  • How precise is neuronal synchronization?

    abstract::Recent work suggests that synchronization of neuronal activity could serve to define functionally relevant relationships between spatially distributed cortical neurons. At present, it is not known to what extent this hypothesis is compatible with the widely supported notion of coarse coding, which assumes that feature...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1995.7.3.469

    authors: König P,Engel AK,Roelfsema PR,Singer W

    更新日期:1995-05-01 00:00:00

  • Parameter Sensitivity of the Elastic Net Approach to the Traveling Salesman Problem.

    abstract::Durbin and Willshaw's elastic net algorithm can find good solutions to the TSP. The purpose of this paper is to point out that for certain ranges of parameter values, the algorithm converges into local minima that do not correspond to valid tours. The key parameter is the ratio governing the relative strengths of the ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.3.363

    authors: Simmen MW

    更新日期:1991-10-01 00:00:00

  • On the Convergence of the LMS Algorithm with Adaptive Learning Rate for Linear Feedforward Networks.

    abstract::We consider the problem of training a linear feedforward neural network by using a gradient descent-like LMS learning algorithm. The objective is to find a weight matrix for the network, by repeatedly presenting to it a finite set of examples, so that the sum of the squares of the errors is minimized. Kohonen showed t...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.2.226

    authors: Luo ZQ

    更新日期:1991-07-01 00:00:00

  • A Resource-Allocating Network for Function Interpolation.

    abstract::We have created a network that allocates a new computational unit whenever an unusual pattern is presented to the network. This network forms compact representations, yet learns easily and rapidly. The network can be used at any time in the learning process and the learning patterns do not have to be repeated. The uni...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.2.213

    authors: Platt J

    更新日期:1991-07-01 00:00:00

  • Parsing Complex Sentences with Structured Connectionist Networks.

    abstract::A modular, recurrent connectionist network is taught to incrementally parse complex sentences. From input presented one word at a time, the network learns to do semantic role assignment, noun phrase attachment, and clause structure recognition, for sentences with both active and passive constructions and center-embedd...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.1.110

    authors: Jain AN

    更新日期:1991-04-01 00:00:00

  • Oscillating Networks: Control of Burst Duration by Electrically Coupled Neurons.

    abstract::The pyloric network of the stomatogastric ganglion in crustacea is a central pattern generator that can produce the same basic rhythm over a wide frequency range. Three electrically coupled neurons, the anterior burster (AB) neuron and two pyloric dilator (PD) neurons, act as a pacemaker unit for the pyloric network. ...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.4.487

    authors: Abbott LF,Marder E,Hooper SL

    更新日期:1991-01-01 00:00:00

  • Weight Perturbation: An Optimal Architecture and Learning Technique for Analog VLSI Feedforward and Recurrent Multilayer Networks.

    abstract::Previous work on analog VLSI implementation of multilayer perceptrons with on-chip learning has mainly targeted the implementation of algorithms like backpropagation. Although backpropagation is efficient, its implementation in analog VLSI requires excessive computational hardware. In this paper we show that, for anal...

    journal_title:Neural computation

    pub_type: 杂志文章

    doi:10.1162/neco.1991.3.4.546

    authors: Jabri M,Flower B

    更新日期:1991-01-01 00:00:00

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