In this paper we describe a novel method for determining synergies between joint motions in reaching movements by hierarchical clustering. A set of recorded elbow and shoulder trajectories is used in a learning algorithm to determine the relationships between angular velocities at elbow and shoulder joints. The learning algorithm is based on optimal criteria for obtaining the hierarchy of descr...

Optical character recognition (OCR) is becoming a powerful tool in the field of Character Recognition, now a days. In the existing globalized environment, OCR can play a vital role in different application fields. Basically, OCR technique converts images into editable format. This technique converts images in the form of documents such as we can edit, modify and store data more safely for long ...

In this study, a new approach based on adaptive neuro-fuzzy inference system (ANFIS) was presented for detection of ophthalmic artery stenosis. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. The ophthalmic arterial Doppler signals...

A precise predictive model is important for obtaining a clear understanding of the changes in dissolved oxygen content in crab ponds. Highly accurate interval forecasting of dissolved oxygen content is fundamental to reduce risk, and three-dimensional prediction can provide more accurate results and overall guidance. In this study, a hybrid three-dimensional (3D) dissolved oxygen content predic...

A neuro-fuzzy system based on a radial basis function network and using support vector learning is considered for non-linear modeling. In order to reduce the number of fuzzy rules, and improve the system interpretability, the proposed method proceeds in two phases. Firstly, the input-output data is clustered according to the subtractive clustering method. Secondly the parameters of the network,...

Reliable prediction of cutting forces is essential for micromilling. In this paper, a fuzzy cutting force modelling method based on subtractive clustering method filters the noise and estimates the instantaneous cutting forces using observations acquired by sensors during cutting experiments. In the experimental case study, four data sets of micromilling cutting force are used. Each data set is...

This paper presents an optimum network structure based on a BBO tuned adaptive neuro-fuzzy inference system (ANFIS) to control active suspension (ASS). The unsupervised learning via Biogeography-Based Optimization (BBO) algorithm is used train the ANFIS network. optimal proportional-integral-derivative controller LQR method generate training data set. base Fuzzy c-means (FCM) clustering applied...

This paper presents the design of the hybrid PID-ANFIS controller for controlling the speed of the Brushless Direct Current Motor (BLDCM). The objective of this work is to obtain the BLDCM speed controller equipment effectively. The hybrid PID-ANFIS controller is a combination of classical PID controller and ANFIS controller. This method is applied to BLDCM speed controller by simulation and im...

Fuzzy clustering is an important tool for analyzing microarray data. A major problem in applying fuzzy clustering method to microarray gene expression data is the choice of parameters with cluster number and centers. This paper proposes a new approach to fuzzy kernel clustering analysis (FKCA) that identifies desired cluster number and obtains more steady results for gene expression data. First...