Search results for: dynamic neural network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4748

Search results for: dynamic neural network

3758 Almost Periodicity in a Harvesting Lotka-Volterra Recurrent Neural Networks with Time-Varying Delays

Authors: Yongzhi Liao

Abstract:

By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of positive almost periodic solution in a delayed Lotka-Volterra recurrent neural networks with harvesting terms. To a certain extent, our work in this paper corrects some result in recent years. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.

Keywords: positive almost periodic solution, Lotka-Volterra, neural networks, Banach fixed point theorem, harvesting

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3757 Retaining Users in a Commercially-Supported Social Network

Authors: Sasiphan Nitayaprapha

Abstract:

A commercially-supported social network has become an emerging channel for an organization to communicate with and provide services to customers. The success of the commercially-supported social network depends on the ability of the organization to keep the customers in participating in the network. Drawing from the theories of information adoption, information systems continuance, and web usability, the author develops a model to explore how a commercially-supported social network can encourage customers to continue participating and using the information in the network. The theoretical model will be proved through an online survey of customers using the commercially-supported social networking sites of several high technology companies operating in the same sector. The result will be compared with previous studies to learn about the explanatory power of the research model, and to identify the main factors determining users’ intention to continue using a commercially-supported social network. Theoretical and practical implications and limitations are discussed.

Keywords: Social network, Information adoption, Information systems continuance, Web usability, User satisfaction.

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3756 Virtualization Technology as a Tool for Teaching Computer Networks

Authors: Dalibor Dobrilovic, Borislav Odadžic

Abstract:

In this paper is being described a possible use of virtualization technology in teaching computer networks. The virtualization can be used as a suitable tool for creating virtual network laboratories, supplementing the real laboratories and network simulation software in teaching networking concepts. It will be given a short description of characteristic projects in the area of virtualization technology usage in network simulation, network experiments and engineering education. A method for implementing laboratory has also been explained, together with possible laboratory usage and design of laboratory exercises. At the end, the laboratory test results of virtual laboratory are presented as well.

Keywords: Computer network simulation software, teaching networking concepts, virtual network laboratory, virtualization technology.

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3755 Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption

Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

Abstract:

In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.

Keywords: Virtual routing function, NFV, resource allocation, minimum power consumption.

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3754 Bi-Criteria Latency Optimization of Intra-and Inter-Autonomous System Traffic Engineering

Authors: K. Vidya, V.Rhymend Uthariaraj

Abstract:

Traffic Engineering (TE) is the process of controlling how traffic flows through a network in order to facilitate efficient and reliable network operations while simultaneously optimizing network resource utilization and traffic performance. TE improves the management of data traffic within a network and provides the better utilization of network resources. Many research works considers intra and inter Traffic Engineering separately. But in reality one influences the other. Hence the effective network performances of both inter and intra Autonomous Systems (AS) are not optimized properly. To achieve a better Joint Optimization of both Intra and Inter AS TE, we propose a joint Optimization technique by considering intra-AS features during inter – AS TE and vice versa. This work considers the important criterion say latency within an AS and between ASes. and proposes a Bi-Criteria Latency optimization model. Hence an overall network performance can be improved by considering this jointoptimization technique in terms of Latency.

Keywords: Inter-Domain Routing , Measurement, OptimizationPerformance, Traffic Engineering.

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3753 Bond Graph and Bayesian Networks for Reliable Diagnosis

Authors: Abdelaziz Zaidi, Belkacem Ould Bouamama, Moncef Tagina

Abstract:

Bond Graph as a unified multidisciplinary tool is widely used not only for dynamic modelling but also for Fault Detection and Isolation because of its structural and causal proprieties. A binary Fault Signature Matrix is systematically generated but to make the final binary decision is not always feasible because of the problems revealed by such method. The purpose of this paper is introducing a methodology for the improvement of the classical binary method of decision-making, so that the unknown and identical failure signatures can be treated to improve the robustness. This approach consists of associating the evaluated residuals and the components reliability data to build a Hybrid Bayesian Network. This network is used in two distinct inference procedures: one for the continuous part and the other for the discrete part. The continuous nodes of the network are the prior probabilities of the components failures, which are used by the inference procedure on the discrete part to compute the posterior probabilities of the failures. The developed methodology is applied to a real steam generator pilot process.

Keywords: Redundancy relations, decision-making, Bond Graph, reliability, Bayesian Networks.

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3752 Dynamic Process Monitoring of an Ammonia Synthesis Fixed-Bed Reactor

Authors: Bothinah Altaf, Gary Montague, Elaine B. Martin

Abstract:

This study involves the modeling and monitoring of an ammonia synthesis fixed-bed reactor using partial least squares (PLS) and its variants. The process exhibits complex dynamic behavior due to the presence of heat recycling and feed quench. One limitation of static PLS model in this situation is that it does not take account of the process dynamics and hence dynamic PLS was used. Although it showed, superior performance to static PLS in terms of prediction, the monitoring scheme was inappropriate hence adaptive PLS was considered. A limitation of adaptive PLS is that non-conforming observations also contribute to the model, therefore, a new adaptive approach was developed, robust adaptive dynamic PLS. This approach updates a dynamic PLS model and is robust to non-representative data. The developed methodology showed a clear improvement over existing approaches in terms of the modeling of the reactor and the detection of faults.

Keywords: Ammonia synthesis fixed-bed reactor, dynamic partial least squares modeling, recursive partial least squares, robust modeling.

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3751 Optimum Tuning Capacitors for Wireless Charging of Electric Vehicles Considering Variation in Coil Distances

Authors: Muhammad Abdullah Arafat, Nahrin Nowrose

Abstract:

Wireless charging of electric vehicles is becoming more and more attractive as large amount of power can now be transferred to a reasonable distance using magnetic resonance coupling method. However, proper tuning of the compensation network is required to achieve maximum power transmission. Due to the variation of coil distance from the nominal value as a result of change in tire condition, change in weight or uneven road condition, the tuning of the compensation network has become challenging. In this paper, a tuning method has been described to determine the optimum values of the compensation network in order to maximize the average output power. The simulation results show that 5.2% increase in average output power is obtained for 10% variation in coupling coefficient using the optimum values without the need of additional space and electro-mechanical components. The proposed method is applicable to both static and dynamic charging of electric vehicles.

Keywords: Coupling coefficient, electric vehicles, magnetic resonance coupling, tuning capacitor, wireless power transfer.

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3750 A General Model for Amino Acid Interaction Networks

Authors: Omar Gaci, Stefan Balev

Abstract:

In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we identify a number of properties of these networks. We compare them to the general small-world network model and we analyze their hierarchical structure.

Keywords: interaction network, protein structure, small-world network.

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3749 Neural Networks Approaches for Computing the Forward Kinematics of a Redundant Parallel Manipulator

Authors: H. Sadjadian , H.D. Taghirad Member, A. Fatehi

Abstract:

In this paper, different approaches to solve the forward kinematics of a three DOF actuator redundant hydraulic parallel manipulator are presented. On the contrary to series manipulators, the forward kinematic map of parallel manipulators involves highly coupled nonlinear equations, which are almost impossible to solve analytically. The proposed methods are using neural networks identification with different structures to solve the problem. The accuracy of the results of each method is analyzed in detail and the advantages and the disadvantages of them in computing the forward kinematic map of the given mechanism is discussed in detail. It is concluded that ANFIS presents the best performance compared to MLP, RBF and PNN networks in this particular application.

Keywords: Forward Kinematics, Neural Networks, Numerical Solution, Parallel Manipulators.

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3748 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle

Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

Abstract:

As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.

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3747 Estimating Localization Network Node Positions with a Multi-Robot System

Authors: Mikko Elomaa, Aarne Halme

Abstract:

A novel method using bearing-only SLAM to estimate node positions of a localization network is proposed. A group of simple robots are used to estimate the position of each node. Each node has a unique ID, which it can communicate to a robot close by. Initially the node IDs and positions are unknown. A case example using RFID technology in the localization network is introduced.

Keywords: Localization network, Multi-robot, RFID, SLAM

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3746 Effects of Natural Frequency and Rotational Speed on Dynamic Stress in Spur Gear

Authors: Ali Raad Hassan, G. Thanigaiyarasu, V. Ramamurti

Abstract:

Natural frequencies and dynamic response of a spur gear sector are investigated using a two dimensional finite element model that offers significant advantages for dynamic gear analyses. The gear teeth are analyzed for different operating speeds. A primary feature of this modeling is determination of mesh forces using a detailed contact analysis for each time step as the gears roll through the mesh. Transient mode super position method has been used to find horizontal and vertical components of displacement and dynamic stress. The finite element analysis software ANSYS has been used on the proposed model to find the natural frequencies by Block Lanczos technique and displacements and dynamic stresses by transient mode super position method. A comparison of theoretical (natural frequency and static stress) results with the finite element analysis results has also been done. The effect of rotational speed of the gears on the dynamic response of gear tooth has been studied and design limits have been discussed.

Keywords: Natural frequency, Modal and transientanalysis, Spur gear, Dynamic stress.

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3745 Supervisory Controller with Three-State Energy Saving Mode for Induction Motor in Fluid Transportation

Authors: O. S. Ebrahim, K. O. Shawky, M. O. Ebrahim, P. K. Jain

Abstract:

Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). Changing the connection of the stator windings from delta to star at no load can achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.

Keywords: Artificial Neural Network, ANN, Energy Saving Mode, ESM, Induction Motor, IM, star/delta switch, supervisory control, fluid transportation, reliability, power quality.

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3744 A New Approach to Design Policies for the Adoption of Alternative Fuel-Technology Powertrains

Authors: Reza Fazeli, Vitor Leal, Jorge Pinho de Sousa

Abstract:

Planning the transition period for the adoption of alternative fuel-technology powertrains is a challenging task that requires sophisticated analysis tools. In this study, a system dynamic approach was applied to analyze the bi-directional interaction between the development of the refueling station network and vehicle sales. Besides, the developed model was used to estimate the transition cost to reach a predefined target (share of alternative fuel vehicles) in different scenarios. Several scenarios have been analyzed to investigate the effectiveness and cost of incentives on the initial price of vehicles, and on the evolution of fuel and refueling stations. Obtained results show that a combined set of incentives will be more effective than just a single specific type of incentives.

Keywords: adoption of Alternative Fuel Vehicles, System Dynamic Analysis, Plug-in Hybrid Vehicles

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3743 High Speed NP-CMOS and Multi-Output Dynamic Full Adder Cells

Authors: Reza Faghih Mirzaee, Mohammad Hossein Moaiyeri, Keivan Navi

Abstract:

In this paper we present two novel 1-bit full adder cells in dynamic logic style. NP-CMOS (Zipper) and Multi-Output structures are used to design the adder blocks. Characteristic of dynamic logic leads to higher speeds than the other standard static full adder cells. Using HSpice and 0.18┬Ám CMOS technology exhibits a significant decrease in the cell delay which can result in a considerable reduction in the power-delay product (PDP). The PDP of Multi-Output design at 1.8v power supply is around 0.15 femto joule that is 5% lower than conventional dynamic full adder cell and at least 21% lower than other static full adders.

Keywords: Bridge Style, Dynamic Logic, Full Adder, HighSpeed, Multi Output, NP-CMOS, Zipper.

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3742 Mirror Neuron System Study on Elderly Using Dynamic Causal Modeling fMRI Analysis

Authors: R. Keerativittatayut, B. Kaewkamnerdpong, J. Laothamatas, W. Sungkarat

Abstract:

Dynamic Causal Modeling (DCM) functional Magnetic Resonance Imaging (fMRI) is a promising technique to study the connectivity among brain regions and effects of stimuli through modeling neuronal interactions from time-series neuroimaging. The aim of this study is to study characteristics of a mirror neuron system (MNS) in elderly group (age: 60-70 years old). Twenty volunteers were MRI scanned with visual stimuli to study a functional brain network. DCM was employed to determine the mechanism of mirror neuron effects. The results revealed major activated areas including precentral gyrus, inferior parietal lobule, inferior occipital gyrus, and supplementary motor area. When visual stimuli were presented, the feed-forward connectivity from visual area to conjunction area was increased and forwarded to motor area. Moreover, the connectivity from the conjunction areas to premotor area was also increased. Such findings can be useful for future diagnostic process for elderly with diseases such as Parkinson-s and Alzheimer-s.

Keywords: Mirror Neuron System (MNS), Dynamic Causal Modeling (DCM), Functional Magnetic Resonance Imaging (fMRI)

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3741 Overload Control in a SIP Signaling Network

Authors: Masataka Ohta

Abstract:

The Internet telephony employs a new type of Internet communication on which a mutual communication is realized by establishing sessions. Session Initiation Protocol (SIP) is used to establish sessions between end-users. For unreliable transmission (UDP), SIP message should be retransmitted when it is lost. The retransmissions increase a load of the SIP signaling network, and sometimes lead to performance degradation when a network is overloaded. The paper proposes an overload control for a SIP signaling network to protect from a performance degradation. Introducing two thresholds in a queue of a SIP proxy server, the SIP proxy server detects a congestion. Once congestion is detected, a SIP signaling network restricts to make new calls. The proposed overload control is evaluated using the network simulator (ns-2). With simulation results, the paper shows the proposed overload control works well.

Keywords: SIP signalling congestion overload control retransmission throughput simulation.

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3740 Categorical Missing Data Imputation Using Fuzzy Neural Networks with Numerical and Categorical Inputs

Authors: Pilar Rey-del-Castillo, Jesús Cardeñosa

Abstract:

There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson-s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.

Keywords: Classifier, imputation techniques, fuzzy systems, fuzzy min-max neural networks.

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3739 Quality and Quantity in the Strategic Network of Higher Education Institutions

Authors: Juha Kettunen

Abstract:

The study analyzes the quality and the size of the strategic network of higher education institutions and the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented from the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high-quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: Higher education, network, research and development, strategic management.

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3738 Dynamic Modeling and Simulation of Industrial Naphta Reforming Reactor

Authors: Gholamreza Zahedi, M. Tarin, M. Biglari

Abstract:

This work investigated the steady state and dynamic simulation of a fixed bed industrial naphtha reforming reactors. The performance of the reactor was investigated using a heterogeneous model. For process simulation, the differential equations are solved using the 4th order Runge-Kutta method .The models were validated against measured process data of an existing naphtha reforming plant. The results of simulation in terms of components yields and temperature of the outlet were in good agreement with empirical data. The simple model displays a useful tool for dynamic simulation, optimization and control of naphtha reforming.

Keywords: Dynamic simulation, fixed bed reactor, modeling, reforming

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3737 Synchronization for Impulsive Fuzzy Cohen-Grossberg Neural Networks with Time Delays under Noise Perturbation

Authors: Changzhao Li, Juan Zhang

Abstract:

In this paper, we investigate a class of fuzzy Cohen- Grossberg neural networks with time delays and impulsive effects. By virtue of stochastic analysis, Halanay inequality for stochastic differential equations, we find sufficient conditions for the global exponential square-mean synchronization of the FCGNNs under noise perturbation. In particular, the traditional assumption on the differentiability of the time-varying delays is no longer needed. Finally, a numerical example is given to show the effectiveness of the results in this paper.

Keywords: Fuzzy Cohen-Grossberg neural networks (FCGNNs), complete synchronization, time delays, impulsive, noise perturbation.

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3736 Adopting Procedural Animation Technology to Generate Locomotion of Quadruped Characters in Dynamic Environments

Authors: Zongyou He, Bashu Tsai, Chinhung Ko, Tainchi Lu

Abstract:

A procedural-animation-based approach which rapidly synthesize the adaptive locomotion for quadruped characters that they can walk or run in any directions on an uneven terrain within a dynamic environment was proposed. We devise practical motion models of the quadruped animals for adapting to a varied terrain in a real-time manner. While synthesizing locomotion, we choose the corresponding motion models by means of the footstep prediction of the current state in the dynamic environment, adjust the key-frames of the motion models relying on the terrain-s attributes, calculate the collision-free legs- trajectories, and interpolate the key-frames according to the legs- trajectories. Finally, we apply dynamic time warping to each part of motion for seamlessly concatenating all desired transition motions to complete the whole locomotion. We reduce the time cost of producing the locomotion and takes virtual characters to fit in with dynamic environments no matter when the environments are changed by users.

Keywords: Dynamic environment, motion synthesis, procedural animation, quadruped locomotion

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3735 The Relationship between Representational Conflicts, Generalization, and Encoding Requirements in an Instance Memory Network

Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

Abstract:

This paper aims to provide an interpretation of artificial neural networks (ANNs) and explore some of its implications. The interpretation views ANNs as a memory which encodes instances of experience. An experiment explores the behavior of encoding and retrieval of instances from memory. A localised representation ANN is created that allows control over encoding and retrieved memory sample size and is experimented with using the MNIST digits dataset. The relationship between input familiarity, conflict within retrieved samples, and error rates is described and demonstrated to be an effective driver for memory encoding. Results indicate that selective encoding and retrieval samples that allow detection of memory conflicts produce optimal performance, and that error rates are normally distributed with input familiarity and conflict. By using input familiarity and sample consistency to guide memory encoding, the number of encoding trials on the dataset were reduced to 18.33% of the training data while maintaining good recognition performance on the test data.

Keywords: Artificial Neural Networks, ANNs, representation, memory, conflict monitoring, confidence.

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3734 Weaknesses and Strengths Analysis over Wireless Network Security Standards

Authors: Daniel Padilla, Edward Guillen

Abstract:

Several wireless networks security standards have been proposed and widely implemented in both business and home environments in order to protect the network from unauthorized access. However, the implementation of such standards is usually achieved by network administrators without even knowing the standards- weaknesses and strengths. The intention of this paper is to evaluate and analyze the impact over the network-s security due to the implementation of the wireless networks security standards WEP, WPA and WLAN 802.1X.

Keywords: 802.1X, vulnerabilities analysis, WEP, wireless security, WPA.

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3733 Dynamic Model and Control of a New Quadrotor Unmanned Aerial Vehicle with Tilt-Wing Mechanism

Authors: Kaan T. Oner, Ertugrul Cetinsoy, Mustafa Unel, Mahmut F. Aksit, Ilyas Kandemir, Kayhan Gulez

Abstract:

In this work a dynamic model of a new quadrotor aerial vehicle that is equipped with a tilt-wing mechanism is presented. The vehicle has the capabilities of vertical take-off/landing (VTOL) like a helicopter and flying horizontal like an airplane. Dynamic model of the vehicle is derived both for vertical and horizontal flight modes using Newton-Euler formulation. An LQR controller for the vertical flight mode has also been developed and its performance has been tested with several simulations.

Keywords: Control, Dynamic model, LQR, Quadrotor, Tilt-wing, VTOL.

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3732 Dynamic Decompression for Text Files

Authors: Ananth Kamath, Ankit Kant, Aravind Srivatsa, Harisha J.A

Abstract:

Compression algorithms reduce the redundancy in data representation to decrease the storage required for that data. Lossless compression researchers have developed highly sophisticated approaches, such as Huffman encoding, arithmetic encoding, the Lempel-Ziv (LZ) family, Dynamic Markov Compression (DMC), Prediction by Partial Matching (PPM), and Burrows-Wheeler Transform (BWT) based algorithms. Decompression is also required to retrieve the original data by lossless means. A compression scheme for text files coupled with the principle of dynamic decompression, which decompresses only the section of the compressed text file required by the user instead of decompressing the entire text file. Dynamic decompressed files offer better disk space utilization due to higher compression ratios compared to most of the currently available text file formats.

Keywords: Compression, Dynamic Decompression, Text file format, Portable Document Format, Compression Ratio.

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3731 Effect of Delay on Supply Side on Market Behavior: A System Dynamic Approach

Authors: M. Khoshab, M. J. Sedigh

Abstract:

Dynamic systems, which in mathematical point of view are those governed by differential equations, are much more difficult to study and to predict their behavior in comparison with static systems which are governed by algebraic equations. Economical systems such as market are among complicated dynamic systems. This paper tries to adopt a very simple mathematical model for market and to study effect of supply and demand function on behavior of the market while the supply side experiences a lag due to production restrictions.

Keywords: Dynamic System, Lag on Supply Demand, Market Stability, Supply Demand Model.

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3730 Voice Disorders Identification Using Hybrid Approach: Wavelet Analysis and Multilayer Neural Networks

Authors: L. Salhi, M. Talbi, A. Cherif

Abstract:

This paper presents a new strategy of identification and classification of pathological voices using the hybrid method based on wavelet transform and neural networks. After speech acquisition from a patient, the speech signal is analysed in order to extract the acoustic parameters such as the pitch, the formants, Jitter, and shimmer. Obtained results will be compared to those normal and standard values thanks to a programmable database. Sounds are collected from normal people and patients, and then classified into two different categories. Speech data base is consists of several pathological and normal voices collected from the national hospital “Rabta-Tunis". Speech processing algorithm is conducted in a supervised mode for discrimination of normal and pathology voices and then for classification between neural and vocal pathologies (Parkinson, Alzheimer, laryngeal, dyslexia...). Several simulation results will be presented in function of the disease and will be compared with the clinical diagnosis in order to have an objective evaluation of the developed tool.

Keywords: Formants, Neural Networks, Pathological Voices, Pitch, Wavelet Transform.

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3729 Face Detection using Gabor Wavelets and Neural Networks

Authors: Hossein Sahoolizadeh, Davood Sarikhanimoghadam, Hamid Dehghani

Abstract:

This paper proposes new hybrid approaches for face recognition. Gabor wavelets representation of face images is an effective approach for both facial action recognition and face identification. Perform dimensionality reduction and linear discriminate analysis on the down sampled Gabor wavelet faces can increase the discriminate ability. Nearest feature space is extended to various similarity measures. In our experiments, proposed Gabor wavelet faces combined with extended neural net feature space classifier shows very good performance, which can achieve 93 % maximum correct recognition rate on ORL data set without any preprocessing step.

Keywords: Face detection, Neural Networks, Multi-layer Perceptron, Gabor wavelets.

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