Deep Stacking Convex Neuro-Fuzzy System and Its On-line Learning

2017 ◽  
pp. 49-59 ◽  
Author(s):  
Yevgeniy Bodyanskiy ◽  
Olena Vynokurova ◽  
Iryna Pliss ◽  
Dmytro Peleshko ◽  
Yuriy Rashkevych
Keyword(s):  
Fuzzy System ◽  
Neuro Fuzzy ◽  
On Line ◽  
On Line Learning

scholarly journals Experimental study of a novel neuro-fuzzy system for on-line handwritten UNIPEN digit recognition

1998 ◽  
Vol 19 (3-4) ◽  
pp. 357-364 ◽  
Author(s):  
E. Gómez Sánchez ◽  
J.A. Gago González ◽  
Y.A. Dimitriadis ◽  
J.M. Cano Izquierdo ◽  
J. López Coronado
Keyword(s):  
Experimental Study ◽  
Fuzzy System ◽  
Digit Recognition ◽  
Neuro Fuzzy ◽  
On Line

scholarly journals ON-LINE NEO-PHASE AUTOENKODER FOR SYSTEMS WITH DEEP LEARNING ON THE BASE OF THE KOLMOGOROV’S NEURO-PHASE NETWORK

2017 ◽  
pp. 60-67
Author(s):  
Є.В. БОДЯНСЬКИЙ ◽  
О.А. ВИНОКУРОВА ◽  
Д.Д. ПЕЛЕШКО ◽  
Ю.М. РАШКЕВИЧ
Keyword(s):  
Neural Networks ◽  
Fuzzy System ◽  
Deep Neural Networks ◽  
Significant Loss ◽  
High Dimensional ◽  
Batch Mode ◽  
Neuro Fuzzy ◽  
Main Disadvantage ◽  
On Line ◽  
Inherent Part

One of the important problem, which is connected with big high dimensional data processing, is the task of their compression without significant loss of information that is contained in this data. The systems, which solve this problem and are called autoencoders, are the inherent part of deep neural networks. The main disadvantage of well-known autoencoders is low speed of learning process, which is implemented in the batch mode. In the paper the two-layered autoencoder is proposed. This system is the modification of Kolmogorov’s neuro-fuzzy system. Thus, in the paper the hybrid neo-fuzzy syste-  mencoder is proposed that has essentially advantages comparatively with conventional neurocompressors-encoders.

Patterns of Implicit Learning Below the Level of Conscious Knowledge

2010 ◽  
Vol 24 (2) ◽  
pp. 91-101 ◽  
Author(s):  
Juliana Yordanova ◽  
Rolf Verleger ◽  
Ullrich Wagner ◽  
Vasil Kolev
Keyword(s):  
Implicit Learning ◽  
Explicit Knowledge ◽  
Implicit Knowledge ◽  
Knowledge Generation ◽  
Sleep Stages ◽  
Implicit Processing ◽  
Implicit Processes ◽  
Late Night ◽  
On Line ◽  
On Line Learning

The objective of the present study was to evaluate patterns of implicit processing in a task where the acquisition of explicit and implicit knowledge occurs simultaneously. The number reduction task (NRT) was used as having two levels of organization, overt and covert, where the covert level of processing is associated with implicit associative and implicit procedural learning. One aim was to compare these two types of implicit processes in the NRT when sleep was or was not introduced between initial formation of task representations and subsequent NRT processing. To assess the effects of different sleep stages, two sleep groups (early- and late-night groups) were used where initial training of the task was separated from subsequent retest by 3 h full of predominantly slow wave sleep (SWS) or rapid eye movement (REM) sleep. In two no-sleep groups, no interval was introduced between initial and subsequent NRT performance. A second aim was to evaluate the interaction between procedural and associative implicit learning in the NRT. Implicit associative learning was measured by the difference between the speed of responses that could or could not be predicted by the covert abstract regularity of the task. Implicit procedural on-line learning was measured by the practice-based increased speed of performance with time on task. Major results indicated that late-night sleep produced a substantial facilitation of implicit associations without modifying individual ability for explicit knowledge generation or for procedural on-line learning. This was evidenced by the higher rate of subjects who gained implicit knowledge of abstract task structure in the late-night group relative to the early-night and no-sleep groups. Independently of sleep, gain of implicit associative knowledge was accompanied by a relative slowing of responses to unpredictable items suggesting reciprocal interactions between associative and motor procedural processes within the implicit system. These observations provide evidence for the separability and interactions of different patterns of processing within implicit memory.

Sign in / Sign up

Export Citation Format

Share Document