Associative learning method in a hypercolumn model
نویسندگان
چکیده
منابع مشابه
Toward a Unified Model of Attention in Associative Learning
Two connectionist models of attention in associative learning, previously used to model human category learning, are shown to have special cases that are essentially equivalent to N. J. Mackintosh's (1975, Psychological Review, 82, 276 298) classic model of attention in animal learning. The models unify formulas for associative weight change with formulas for attentional change, under a common ...
متن کاملAssociative Learning Using Ising-Like Model
In this paper, a new computational model of associative learning is proposed, which is based on the Ising model. Application of the stochastic gradient descent algorithm to the proposed model yields an on-line learning rule. Next, it is shown that the obtained new learning rule generalizes two well-known learning rules, i.e., the Hebbian rule and the Oja's rule. Later, the fashion of incorporat...
متن کاملLearning about environmental geometry: an associative model.
K. Cheng (1986) suggested that learning the geometry of enclosing surfaces takes place in a geometric module blind to other spatial information. Failures to find blocking or overshadowing of geometry learning by features near a goal seem consistent with this view. The authors present an operant model in which learning spatial features competes with geometry learning, as in the Rescorla-Wagner m...
متن کاملA New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain
Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...
متن کاملA New Hybrid Model for Associative Reinforcement Learning
In this paper, a new model, addressing the Associative Reinforcement Learning (ARL) problem, based on learning automata and self organizing map is proposed. The model consists of two layers. The First layer comprised of a SOM which is utilized to quantize the state (context) space and the second layer contains of a team of learning automata which is used to select an optimal action in each stat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Artificial Life and Robotics
سال: 2007
ISSN: 1433-5298,1614-7456
DOI: 10.1007/s10015-006-0404-x