麻省理工大学出版社
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作者:Gavin Jenkins , Paul Tupper
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1961-1982麻省理工大学出版社
摘要:Transposition is a tendency for organisms to generalize relationships between stimuli in situations where training does not objectively reward relationships over absolute, static associations. Transposition has most commonly been explained as either conceptual understanding ...
作者:Tomoumi Takase , Satoshi Oyama , Masahito Kurihara
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.2005-2023麻省理工大学出版社
摘要:We present a comprehensive framework of search methods, such as simulated annealing and batch training, for solving nonconvex optimization problems. These methods search a wider range by gradually decreasing the randomness added to the standard gradient descent method. The formul...
作者:Xiaopeng Guo , Rencan Nie , Jinde Cao ...
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1775-1800麻省理工大学出版社
摘要:As the optical lenses for cameras always have limited depth of field, the captured images with the same scene are not all in focus. Multifocus image fusion is an efficient technology that can synthesize an all-in-focus image using several partially focused images. Previous method...
作者:Yung-Kyun Noh , Masashi Sugiyama , Song Liu ...
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1930-1960麻省理工大学出版社
摘要:Nearest-neighbor estimators for the Kullback-Leiber (KL) divergence that are asymptotically unbiased have recently been proposed and demonstrated in a number of applications. However, with a small number of samples, nonparametric methods typically suffer from large estimation bia...
作者:Irina Higgins , Simon Stringer , Jan Schnupp
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1801-1829麻省理工大学出版社
摘要:It is well known that auditory nerve (AN) fibers overcome bandwidth limitations through the volley principle, a form of multiplexing. What is less well known is that the volley principle introduces a degree of unpredictability into AN neural firing patterns that may be affecting ...
作者:Yazhou Hu , Bailu Si
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1983-2004麻省理工大学出版社
摘要:We propose a neural network model for reinforcement learning to control a robotic manipulator with unknown parameters and dead zones. The model is composed of three networks. The state of the robotic manipulator is predicted by the state network of the model, the action policy is...
作者:George Dimitriadis , Joana P. Neto , Adam R. Kampff
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1750-1774麻省理工大学出版社
摘要:Electrophysiology is entering the era of big data. Multiple probes, each with hundreds to thousands of individual electrodes, are now capable of simultaneously recording from many brain regions. The major challenge confronting these new technologies is transforming the raw data i...
作者:Vitaly L. Galinsky , Antigona Martinez , Martin P. Paulus ...
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1725-1749麻省理工大学出版社
摘要:In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using e...
作者:Alan Paris , Azadeh Vosoughi , Stephen A. Berman ...
来源:[J].Neural Computation(IF 1.76), 2018, Vol.30 (7), pp.1830-1929麻省理工大学出版社
摘要:In this letter, we perform a complete and in-depth analysis of Lorentzian noises, such as those arising from and channel kinetics, in order to identify the source of –type noise in neurological membranes. We prove that the autocovariance of Lorentzian noise depends solely on...
作者:Kate Nelischer
来源:[J].Design Issues, 2018, Vol.34 (3), pp.108-110麻省理工大学出版社

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