Systems in neural networks

This thesis develops a flexible customer behavior analysis system, including essential head pose estimation or F-formation modules. This system will be evaluated in an actual retail store. Further, after studying the system, realizing the mentioned problems of the head pose problem, we also propose a process to collect the head pose dataset and multi-task deep neural network model, fusing face detection and head pose estimation to yield face position and head pose at the same time.

72p khanhchi0912 12-04-2024 2 2   Download

Intrusion Detection (ID) is one of the active branches in network security research field. Many technologies, such as neural networks, fuzzy logic and genetic algorithms have been applied in intrusion detection and the results are varied. In this thesis, an Artificial Immune System (AIS) based intrusion detection is explored. AIS is a bio-inspired computing paradigm that has been applied in many different areas including intrusion detection.

74p runthenight07 01-03-2023 6 2   Download

Research aims: This thesis is concerned with the stability of some classes of nonlinear time-delay systems in neural networks. Investigating the problem of stability of non-autonomous neural networks with heterogeneous time-varying delays in the effect of destablizing impulses. Stabilizing Hopfiled neural networks with proposition delays subject to stabilizing and destablizing impulsive effects simultaneously.

27p tunelove 10-06-2021 21 3   Download

The techniques of supervised ones are applied to the data domain in order to have a comparison between the evaluated system of POSSUM and the advantage of Neural network. The comparisons are based on the rate of mortality and morbidity of patients. The outcome set of unsupervised learning techniques is compared to the results of supervised ones.

8p tamynhan8 04-11-2020 19 1   Download

The research works were published at international paper mainly focused on diagnosing epilepsy sleep disorders, coma and brain death, stress, depresssion pathological… in automation field as spelling, eye blink, head movement, mental arithmetic… this were performed by offline, no mainly focus on resolving in realtime and in control automation field.

33p gaocaolon6 30-07-2020 43 3   Download

This paper intends to present the System Dynamics (SD) as a novel method to simulate the thrust force developed during drilling of GFRP composites. Good quality holes are extremely fundamental so as to accomplish equally good joints amid creation of components prepared from composite for better execution.

9p lucastanguyen 01-06-2020 10 2   Download

The thesis aims to propose some control techniques for mobile target Robot-camera. After that, I studied some of the torque control techniques of joints for the Robot-camera system sticking to the mobile target and the Robot-camera system, paying attention to the motivating motor sticking to the mobile target. Finally, the author also proposed some control algorithms for Robotic-camera arm system with irregular model, external noise and preventing system degradation, using nonlinear sliding controller (TSMC) in combination with Artificial neural networks to estimate uncertain numbers.

31p xacxuoc4321 09-07-2019 27 2   Download

This paper proposes a new control method for Pan-Tilt stereo camera system to track a moving object when there are many uncertainties in the parameters of both camera and Pan-Tilt platform. If a pair of cameras placed on the Pan-Tilt robot, it is unnecessary for its installation location to be determined accurately.

16p dieutringuyen 07-06-2017 32 1   Download

After modeling and analyzing the system, this paper suggests a new control method using an online learning neural network in closed-loop to control the Pan-Tilt platform that moves the Camera to keep tracking an unknown moving object.

11p dieutringuyen 07-06-2017 53 5   Download

In this paper we address the problem of extracting features relevant for predicting protein±protein interaction sites from the three-dimensional structures of protein complexes. Our approach is based on information about evolutionary con-servation and surface disposition. We implement a neural network based system, which uses a cross validation proce-dure and allows the correct detection of 73% of the residues involved in protein interactions in a selected database comprising 226 heterodimers.

6p research12 29-04-2013 29 2   Download

EURASIP Journal on Applied Signal Processing 2003:12, 1229–1237 c 2003 Hindawi Publishing Corporation Nonlinear System Identification Using Neural Networks Trained with Natural Gradient Descent Mohamed Ibnkahla Electrical and Computer Engineering Department, Queen’s University, Kingston, Ontario, Canada K7L 3N6 Email: mohamed.ibnkahla@ece.queensu.ca Received 13 December 2002 and in revised form 17 May 2003 We use natural gradient (NG) learning neural networks (NNs) for modeling and identifying nonlinear systems with memory.

9p sting12 10-03-2012 42 5   Download

EURASIP Journal on Applied Signal Processing 2003:9, 890–901 c 2003 Hindawi Publishing Corporation An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System Javad Haddadnia Engineering Department, Tarbiat Moallem University of Sabzevar, Sabzevar, Khorasan 397, Iran Email: haddadnia@sttu.ac.ir Majid Ahmadi Electrical and Computer Engineering Department, University of Windsor, Windsor, Ontario, Canada N9B 3P4 Email: ahmadi@uwindsor.

12p sting12 10-03-2012 37 6   Download

Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008, Article ID 468693, 7 pages doi:10.1155/2008/468693 Research Article Comparing Robustness of Pairwise and Multiclass Neural-Network Systems for Face Recognition J. Uglov, L. Jakaite, V. Schetinin, and C. Maple Computing and Information System Department, University of Bedfordshire, Luton LU1 3JU, UK Correspondence should be addressed to V. Schetinin, vitaly.schetinin@beds.ac.uk Received 16 June 2007; Revised 28 August 2007; Accepted 19 November 2007 Recommended by Konstantinos N.

7p dauphong18 24-02-2012 60 3   Download

Disorders of Gait The heterogeneity of gait disorders observed in clinical practice reflects the large network of neural systems involved in the task. There is the potential for abnormalities to develop, and walking is vulnerable to neurologic disease at every level. Gait disorders have been classified descriptively, based on the abnormal physiology and biomechanics. One problem with this approach is that many failing gaits look fundamentally similar. This overlap reflects common patterns of adaptation to threatened balance stability and declining performance.

5p ongxaemnumber1 29-11-2010 63 2   Download

The explosive growth of distributed computing has been fuelled by many factors. Applications such as video conferencing, teleoperation and most notably the World Wide Web are placing ever more demanding requirements on their underlying communication systems. Having never been designed to support such diverse communication patterns these systems are failing to provide appropriate services to individual applications. Artificial neural networks have been used in areas of communication systems including signal processing and call management (Kartalopolus, 1994)....

21p tienvovan 11-09-2010 70 5   Download

Convergence of Online Learning Algorithms in Neural Networks An analysis of convergence of real-time algorithms for online learning in recurrent neural networks is presented. For convenience, the analysis is focused on the real-time recurrent learning (RTRL) algorithm for a recurrent perceptron. Using the assumption of contractivity of the activation function of a neuron and relaxing the rigid assumptions of the fixed optimal weights of the system, the analysis presented is general and is applicable to a wide range of existing algorithms....

9p doroxon 12-08-2010 89 8   Download

Stability Issues in RNN Architectures Perspective The focus of this chapter is on stability and convergence of relaxation realised through NARMA recurrent neural networks. Unlike other commonly used approaches, which mostly exploit Lyapunov stability theory, the main mathematical tool employed in this analysis is the contraction mapping theorem (CMT), together with the fixed point iteration (FPI) technique. This enables derivation of the asymptotic stability (AS) and global asymptotic stability (GAS) criteria for neural relaxive systems.

19p doroxon 12-08-2010 103 8   Download

Neural Networks as Nonlinear Adaptive Filters Perspective Neural networks, in particular recurrent neural networks, are cast into the framework of nonlinear adaptive filters. In this context, the relation between recurrent neural networks and polynomial filters is first established. Learning strategies and algorithms are then developed for neural adaptive system identifiers and predictors. Finally, issues concerning the choice of a neural architecture with respect to the bias and variance of the prediction performance are discussed....

24p doroxon 12-08-2010 77 10   Download

Recurrent Neural Networks Architectures Perspective In this chapter, the use of neural networks, in particular recurrent neural networks, in system identification, signal processing and forecasting is considered. The ability of neural networks to model nonlinear dynamical systems is demonstrated, and the correspondence between neural networks and block-stochastic models is established. Finally, further discussion of recurrent neural network architectures is provided.

21p doroxon 12-08-2010 95 13   Download

Fundamentals Adaptive systems are at the very core of modern digital signal processing. There are many reasons for this, foremost amongst these is that adaptive filtering, prediction or identification do not require explicit a priori statistical knowledge of the input data. Adaptive systems are employed in numerous areas such as biomedicine, communications, control, radar, sonar and video processing (Haykin 1996a).

21p doroxon 12-08-2010 88 17   Download