Data Analysis for Investment & Control

Hardware Implementation of a Neural Network Controller on FPGA for a Humanoid Robot Arm Abstract – This paper presents the design and the implementation of the neural network controller for a humanoid robot arm, the ROBOKER whose purpose is to work on behalf of of human workers. The radial basis function network is implemented on a field programmable gate array(FPGA). The design of the floating ..

Implementation of the RBF Neural Chip with the On-line Learning Back-Propagation Algorithm Abstract—This article presents the hardware implementation of the Radial Basis Function (RBF) neural network whose internal weights are updated in the real time fashion by the back-propagation algorithm. The floating-point processor is designed on a field programmable gat array (FPGA) chip to execute nonli..

Implementation of neural network hardware based on a floating point operation in an FPGA Abstract : This paper presents a hardware design and implementation of the radial basis function (RBF) neural network (NN) by the hardware description language. Due to its nonlinear characteristics, it is very difficult to implement for a system with integer-based operation. To develop nonlinear functions su..

Hardware Implementation of Nonlinear PID Controller with FPGA Based on Floating Point Operation for 6-DOF Manipulator Robot Arm Abstract: This paper presents the FPGA implementation of nonlinear PID controllers for humanoid robot arms. To design the nonlinear PID controller on an FPGA chip, nonlinear functions as well as the conventional PID control algorithm have to be implemented by the hardwa..

비선형 함수 연산을 위한 FPGA 기반의 부동 소수점 프로세서의 설계 (Design of a Floating Point Processor for Nonlinear Functions on an Embedded FPGA) Abstract - This paper presents the hardware design of a 32bit floating point based processor. The processor can perform nonlinear functions such as sinusoidal functions, exponential functions, and other nonlinear functions. Using the Taylor series and the Newton - Raphson met..