Objective: To investigate how learning induced increases in stability on a syncopation task are manifest in the dynamics of cortical activity. Method: Magnetoencephalography was recorded from 143 sensors (CTF Systems, Inc). A pre-training procedure determined the critical frequency (Fc) for each subject (n ˆ 4). Subjects either syncopated or synchronized to a metronome that increased in frequen...

OBJECTIVE To investigate how learning induced increases in stability on a syncopation task are manifest in the dynamics of cortical activity. METHOD Magnetoencephalography was recorded from 143 sensors (CTF Systems, Inc). A pre-training procedure determined the critical frequency (F(c)) for each subject (n=4). Subjects either syncopated or synchronized to a metronome that increased in frequen...

Generative adversarial networks (GANs) are highly effective unsupervised learning frameworks that can generate very sharp data, even for data such as images with complex, highly multimodal distributions. However GANs are known to be very hard to train, suffering from problems such as mode collapse and disturbing visual artifacts. Batch normalization (BN) techniques have been introduced to addre...

[Purpose] This study examined the effects of neuromuscular training on knee joint stability after anterior cruciate ligament reconstruction. [Subjects and Methods] The subjects were 16 adults who underwent arthroscopic anterior cruciate reconstruction and neuromuscular training. The Lysholm scale was used to assess functional disorders on the affected knee joint. A KT-2000 arthrometer was used ...

Computational Intelligence combines neural network, fuzzy systems and evolutional computing. Neurofuzzy integrated system utilizes features of both Neural and Fuzzy networks together for better results by which generalization of the unseen data from seen data by forming the fuzzy rules and training. In this project training of the system with training data which usually is 70% of the whole avai...

[Purpose] This study examined the effects of an ankle-foot orthosis worn during balance training on lower limb muscle activity and static balance of chronic stroke patients. [Subjects] The subjects were twenty-five inpatients receiving physical therapy for chronic stroke. [Methods] The chronic stroke patients were divided into two groups: thirteen patients were assigned to the ankle-foot orthos...

Stability is a general notion that quantifies the sensitivity of a learning algorithm’s output to small change in the training dataset (e.g. deletion or replacement of a single training sample). Such conditions have recently been shown to be more powerful to characterize learnability in the general learning setting under i.i.d. samples where uniform convergence is not necessary for learnability...

Since the creation of Generative Adversarial Networks (GANs), much work has been done to improve their training stability, their generated image quality, their range of application but nearly none of them explored their self-training potential. Self-training has been used before the advent of deep learning in order to allow training on limited labelled training data and has shown impressive res...

Since the creation of Generative Adversarial Networks (GANs), much work has been done to improve their training stability, their generated image quality, their range of application but nearly none of them explored their self-training potential. Self-training has been used before the advent of deep learning in order to allow training on limited labelled training data and has shown impressive res...

a new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. we use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. then, we linearized this identified model at each sampling time to have an approximate linear time varying system. in order to stabilize...