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Edwar Jacinto, G.
- A CORDIC based Configurable Fixed-Point Design on FPGA using Minimal Hardware
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Authors
Affiliations
1 Technological Faculty, District University Francisco José de Caldas, Bogotá D.C., Colombia
1 Technological Faculty, District University Francisco José de Caldas, Bogotá D.C., Colombia
Source
Indian Journal of Science and Technology, Vol 10, No 24 (2017), Pagination:Abstract
Objectives: To design a COordinate Rotation DIgital Computer (CORDIC) based electrical signal processing system for efficient and minimalist electrical power processing. Methods: This stage of assessment describes the design and performance of a true RMS (Root-Mean Square) voltage meter on Xilinx SPARTAN 3E 1600 FPGA. Findings: The effectiveness of the proposed designs is assessed through FPGA implementations and error simulations. Measurement results show that the model can reproduce behaviors similar to the original model traditional use of multipliers, but with less resource consumption (hardware and processing time). Novelty: The use of CORDIC to reduce the computational cost of the algorithm, and its implementation in an embedded system.Keywords
CORDIC, Embedded System, FPGA, Real-Time, True RMSFull Text
- Identifying Deep Regression Models for Time Series Prediction of Continuous Data in an Anthropomorphic Robot Telecontrol System
Abstract Views :186 |
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Authors
Affiliations
1 Universidad Distrital Francisco Jose de Caldas, Bogota D.C., CO
1 Universidad Distrital Francisco Jose de Caldas, Bogota D.C., CO
Source
Indian Journal of Science and Technology, Vol 11, No 31 (2018), Pagination: 1-11Abstract
Objectives: To construct regression models in order to predict the behavior of data produced by motion sensors and muscle activity sensors linked to a human arm, with the intention of coordinating the movement of a robot. Methods: We use a LSTM (Long Short-Term Memory) network setup as a transfer learning problem where a sequence vector is generated and then a probability distribution and a set of real values are output and trained with separate cost functions. Findings: Evaluations are based on the precision accuracy of the algorithms applied to the data provided by the Myo Gesture Control Armband (Thalmic Labs) sensor used by different people with equivalent arm movements. These evaluations show a predictable behavior of the movements independently of the user. Novelty: The use of deep learning to solve a difficult problem of predicting time series avoiding overfitting.Full Text
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