Biological Feedback Controller Design for Handwriting Model
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 11
Abstract
This paper deals with a feedback controller of PD (proportional, derivative) type applied to the process of handwriting. The considered model for this study describes the behavior of the system “hand and pen” to forearm muscles forces, applied for the production of handwriting. The applied approach considers memory recall of error signal between model outputs and experimental data to reach a desired trajectory position, a rapid dynamic and stable model response. The control technique is applied in order to expand the handwriting model response to a larger database of graphic traces. The obtained results illustrated the reliability of closed loop control to command the handwriting system, and to ensure its robustness against unknown inputs such as muscles forces that could vary from an individual to another and increase model complexity.
Authors and Affiliations
Mariem BADRI, Ines CHIHI, Afef Abdelkrim
A Tool for C++ Header Generation
This paper presents a novel approach in the field of C++ development for increasing performance by reducing cognitive overhead and complexity, which results in lower costs. C++ code is split into header and cpp files. Th...
The Throughput Flow Constraint Theorem and its Applications
The paper states and proves an important result related to the theory of flow networks with disturbed flows:“the throughput flow constraint in any network is always equal to the throughput flow constraint in its dual net...
Organizing Multipath Routing in Cloud Computing Environments
One of the objectives of organizing cloud systems is to ensure effective access to remote resources by optimizing traffic engineering (TE) procedures. This paper considers the traffic engineering problem in a cloud envir...
LOAD BALANCING WITH NEURAL NETWORK
This paper discusses a proposed load balance technique based on artificial neural network. It distributes workload equally across all the nodes by using back propagation learning algorithm to train feed forward Artificia...
Personalizing of Content Dissemination in Online Social Networks
Online social networks have seen a rapid growth in recent years. A key aspect of many of such networks is that they are rich in content and social interactions. Users of social networks connect with each other and formin...