IJON 2002 - PDF Preprint Papers

IJON 2002

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IJON
2002

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NEURObjects: an object-oriented library for neural network development

13 years 4 months ago

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NEURObjects is a set of C++ library classes for neural network development, exploiting the potentialities of object-oriented design and programming. The main goal of the library c...

Giorgio Valentini, Francesco Masulli

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Id	Views	Title	Status

1	219	NEURObjects: an object-oriented library for neural network development	claim
2	185	An image retrieval system by impression words and specific object names - IRIS	claim
3	154	Nonlinear model predictive control of a cutting process	claim
4	138	Blind deconvolution using temporal predictability	claim
5	130	Error-backpropagation in temporally encoded networks of spiking neurons	claim
6	128	Extraction of a source from multichannel data using sparse decomposition	claim
7	123	N-bit parity neural networks: new solutions based on linear programming	claim
8	120	The recognition and analysis of animate objects using neural networks and active contour models	claim
9	112	Kernel methods: a survey of current techniques	claim
10	105	Separation of sources using simulated annealing and competitive learning	claim
11	104	Power and the limits of reactive agents	claim
12	103	RBF networks training using a dual extended Kalman filter	claim
13	101	Correlated input spike trains and their effects on the response of the leaky integrate-and-fire neuron	claim
14	100	A computational neuroscience account of visual neglect	claim
15	99	Asymptotic behaviors of population codes	claim
16	98	Blind deconvolution by simple adaptive activation function neuron	claim
17	91	Local averaging optimization for chaotic time series prediction	claim
18	91	Information transmission by stochastic synapses with short-term depression: neural coding and optimization	claim
19	90	Linearly decodable functions from neural population codes	claim
20	88	Curved feature metrics in models of visual cortex	claim
21	85	Learning statistically efficient features for speaker recognition	claim
22	85	Independent components of natural images under variable compression rate	claim
23	84	On the generative probability density model in the self-organizing map	claim
24	83	Population coding with unreliable spikes	claim
25	83	Modeling temporal combination selective neurons of the songbird	claim
26	83	An adaptive spike-timing-dependent plasticity rule	claim
27	82	Functional imaging and neuronal information processing	claim
28	80	Novel dynamics of dendritic integration in the high conductance state of cortical neurons	claim
29	79	Capacity of perirhinal cortex network for recognising frequently repeating stimuli	claim
30	78	External termination of recurrent bursting in a model of connected local neural sub-networks	claim
31	75	Problem-solving behavior in a system model of the primate neocortex	claim
32	74	Optimal spontaneous activity in neural network modeling	claim
33	72	Modeling large cortical networks with growing self-organizing maps	claim
34	71	Generation of the respiratory rhythm: state-dependency and switching	claim
35	69	From single-trial EEG to brain area dynamics	claim
36	69	Point-conductance models of cortical neurons with high discharge variability	claim
37	69	A computationally efficient abstraction of long-term potentiation	claim
38	67	Synfire chain in a balanced network	claim
39	67	Test of spike-sorting algorithms on the basis of simulated network data	claim
40	65	A general framework for neurobiological modeling: an application to the vestibular system	claim
41	65	Recognizing the gist of a visual scene: possible perceptual and neural mechanisms	claim
42	64	Software engineering tools and approaches for neuroinformatics: the design and implementation of the View-Primitive Data Model framework (VPDMf)	claim
43	61	Mechanistic modeling of the retinogeniculate circuit in cat	claim
44	59	Spike-time reliability of periodically driven integrate-and-fire neurons	claim
45	52	Minimal MLPs do not model the XOR logic	claim
46	51	Scaling a slow-wave sleep cortical network model using NEOSIM	claim
47	45	Evolving field models for inhibition effects in early vision	claim

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