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Sleep stage scoring is the first step to diagnostic of sleep disorders and it is scored by the conventional method known as the visual sleep stage scoring based on human. To assist the sleep physician in evaluating of patients, a new automatic sleep stage classification system needs to be developed. So this is the aim of this work based on Electroencephalography (EEG) and Electrocardiography (ECG)...
This paper presents the inverse kinematic solutions based on neural networks. General neural network approaches use data of the end-effector positions as an input and angle joints as an output to train the neural network for mapping the input to the output. However, the proposed method creates the custom networks from forward kinematic equations. This special structure makes the network like a position...
This paper presents the inverse kinematics solution using the neural network for a robotic arm in 3-dimension. This paper creates neural networks to represent x, y and z position of the end-effector in the forward kinematics equations. The structure of the network has 4 layers; input layer, 2 hidden layers, and output layer. The input and output layers are defined as robotic arm angle and position...
A meal assistant robotic arm is necessary for disable people who cannot move by themselves such as paralysis patients, severely handicapped people, etc. Several research articles have been proposed. However, the system designs for the meal assistant robotic arm have been found for a small number of the improvements. Therefore, this paper presents a detailed study to innovate the meal assistant robotic...
This paper presents the canonical correlation analysis (CCA) method for dimensional reduction of sleep apnea features extracted from the electrocardiogram single lead. The feature extraction belong to the linear and nonlinear techniques of variance of heart rhythm or heart rate variability and respiratory waveform from electrocardiography signal. These are benefit to evaluate the sleep apnea in noninvasive...
This paper presents a detailed study to demonstrate the online tuning dynamic neural network PID controller to improve a joint angle position output performance of 4-joint robotic arm. The proposed controller uses a new updating weight rule model of the neural network architecture using multi-loop calculation of the fusion of the gradient algorithm with the cubature Kalman filter (CKF) which can optimize...
The Proportional Integral Derivative (PID) controller is widely used in the industrial control application, which is only suitable for the single input/single output (SISO) with known-parameters of the linear system. However, many researchers have been proposed the neural network controller based on PID (NNPID) to apply for both of the single and multi-variable control system but the NNPID controller...
This paper presents a new method to improve image quality by using adaptive window size multi-focus image fusion based on Sum of Modified Laplacian (SML). The method employs the focus measurement to select the best in focus area of the input images. Then combine these areas to be the output image which all areas are in focus. The size of the window for the focus measurement is adjustable. The criterion...
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