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A novel method for correlated short-term fading simulation is presented and analyzed in this paper. Proposed solution is based on artificial neural networks. In order to obtain an adequate training data set, extensive measurements of the electric field strength were carried out in an indoor environment. Due to its modular architecture, the proposed simulator could be used to generate potentially any...
In recent years, progress in the field of artificial neural networks provides a very important tool for complex problems in pattern recognition, data mining and medical diagnosis. The training algorithms of neural networks play an important role for adjustment the network parameters. Different algorithms have been presented for training neural networks; the most common one is the use of gradient descent...
In this paper, the theme of Exponential Synchronization (ES) for a new class of Complex Dynamical Networks (CDN) with hybrid Time-Varying Delay (TVD) and Non-Time-Varying Delay (NTVD) nodes is investigated by using coupling Periodically Intermittent Pinning Control (PIPC). Based on the Lyapunov Stability Theory (LST), Kronecker product rules and PIPC method, sufficient conditions for ES and PIPC criteria...
In this paper, a novel neural network (NN) adaptive dynamic programming (ADP) control scheme for distributed parameter systems (DPS) governed by parabolic partial differential equations (PDE) is introduced in the presence of control constraints and unknown system dynamics. First, Galerkin method is utilized to develop a relevant reduced order system which captures the dominant dynamics of the DPS...
This paper offers details on a particular type of Complex Valued Neural Networks, which are Artificial Neural Networks that accept complex-valued inputs and use complex numbers for the values of the internal parameters. The functioning in the complex numbers domain grants CVNNs more computational power than classical ANNs. Phase-Based Neurons (PBNs) are simple CVNNs which use for the internal weights...
This paper proposes a novel approach for automatic estimation of four important traits of speakers, namely age, height, weight and smoking habit, from speech signals. In this method, each utterance is modeled using the i-vector framework which is based on the factor analysis on Gaussian Mixture Model (GMM) mean supervectors, and the Non-negative Factor Analysis (NFA) framework which is based on a...
This paper proposes a fuzzy interval type 2 logic based autonomous lateral flight controller for UAVs (unmanned aerial vehicles). The implementation framework utilizes MAT-LAB's standard configuration and the Aerosim Aeronautical Simulation Block Set which provides a complete set of tools for rapid development of detailed 6 degree-of-freedom nonlinear generic manned/unmanned aerial vehicle models...
The presence of metallic particles can adversely affect the reliability of Gas-Insulated Substation (GIS) by initiating partial discharges (PDs). Therefore, the investigation of PD characteristics and particle size and position on the spacer surface are the significant steps toward the reliability improvement of the GIS equipments. This paper presents the use of Back-Propagation Artificial Neural...
Predicting students' academic achievement with high accuracy has an important vital role in many academic disciplines. Most recent studies indicate the important role of the data type selection. They also attempt to understand individual students more deeply by analyzing questionnaire for a particular purpose. The present study uses free-style comments written by students after each lesson, to predict...
This paper presents an improved direct torque control of Permanent magnetic synchronous motor (PMSM) based on neural network (NN) and fuzzy logic (FL) technique. The major problem that is usually associated with direct torque control (DTC) drive is the high torque ripple. This paper proposes to replace the conventional selector switches statements of the voltage inverter by a selector based on artificial...
This study aimed to propose, a different architecture of a collision detection neural network (DCNN). The ability to detect and avoid collision is very important for mobile intelligent machines. However many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach...
This paper proposes a new method to provide personalized tour recommendation for museum visits. It combines an optimization of preference criteria of visitors with an automatic extraction of artwork importance from museum information based on Natural Language Processing using textual energy. This project includes researchers from computer and social sciences. Some results are obtained with numerical...
Hashtags are useful for categorizing and discovering content and conversations in online social networks. However, assigning hashtags requires additional user effort, hampering their widespread adoption. Therefore, in this paper, we introduce a novel approach for hashtag recommendation, targeting English language tweets on Twitter. First, we make use of a skip-gram model to learn distributed word...
The Student name Identification System (SIS) proposed here was investigated for English and Thai languages combined. The proposed system recognises each name by using an approach for whole word recognition. In the proposed system, the Gaussian Grid Feature (GGF), and Modified Direction Feature (MDF), together with a proposed hybrid feature extraction technique called Water Reservoir, Loop and Gaussian...
The voice conversion system modifies the speaker specific features of the source speaker so that it sounds like a target speaker speech. The voice individuality of the speech signal is characterized at various levels such as shape of the glottal excitation, shape of the vocal tract and the long term prosodic features. In this work, Line Spectral Frequencies (LSF) are used to represent the shape of...
In telephony applications, artificial bandwidth extension (ABE) can be applied to narrowband (NB) calls for speech quality and intelligibility enhancement. However, high-band extension is challenging due to insufficient mutual information between the lower and upper frequency band in speech. Estimation errors particularly of fricatives /s, z/ are the consequence leading to annoying artifacts, such...
A Neural network with a feed-forward structure with one input, one hidden and one output layer can be presented as a hierarchical two-level structure with two independent subnetworks on both the first and the second level. This process is known as decomposition of an Artificial Neural Network (ANN) into two sub-networks. Two target functions are defined: the output target function Ψ, which defines...
Emotion signifies the core value when a person comes in contact with multidimensional situation. Primary emotion has a capacity to observe when subject is contact with varying arising situation. Our research aims to present how primary emotion help to predict the human blood pressure (BP). Facebook is a Social Networking Sites (SNS) that provide emotionally rich environments and one of the most popular...
The present study proposes prediction approaches of student's grade based on their comments data. Students describe their learning attitudes, tendencies and behaviors by writing their comments freely after each lesson. The main difficulty of this research is to predict students' performance by separately using two class data in each lesson. Although students learn the same subject, there exist differences...
Planetary gearbox is a common mechanical component and is widely used to transmit power and change speed and/or direction in rotary aircrafts. The part failure of planetary gearbox is one of the main causes for the helicopter accidents. The need to identify the level of developing damage in part is central to reduce mechanically induced failures. An approach based on grey relational analysis(GRA)...
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