Sharif Digital Repository

We investigate hot spot effects on increasing THz emission of the frequency modes in a square mesa structure with constant hot spot size in different positions, without applying magnetic field. We show that in the presence of hot spot at any position, the average of emitted power intensity level is increased. The frequency modes that the position of their field concentration is more matched with hot spot position are more excited. Accordingly, in the case with hot spot located at center of a-axis or b-axis, frequency modes TM(m,n) with even indices m or n is more excited and in the case in which hot spot is located at the corner of a-axis or b-axis, frequency modes TM(m,n) with odd indices m... 

Coming up with a model which matches biological observations more closely has always been one of the main challenges in the field of artificial neural networks. Lately, an ionic model of reservoir networks containing spiking neurons (ILS-based reservoir network) has been proposed which seems to replicate some of the biological processes we have observed up until now. This paper presents a local learning rule for the ILS-based reservoir inspired by the biological fact that each incoming stimulus causes the formation of new dendritic spines, producing new synapses. This property may result in a higher degree of neuroplasticity, leading to a higher learning capacity. To evaluate the proposed... 

This paper proposes a new method based on Particle Swarm Optimization (PSO) for feature selection in phonemes sound classification. Inspired of biologist's studies, each particle is represented by filterbank which is motivated by human hearing. Thus, we propose a technique in which PSO is used to extract audio features similar to human's ear in order to achieve better classification. We use PSO technique for optimizing particle's filterbank in order to classify sound signals accurately. Then, feature extraction is done by using particle's information. Moreover, a classification method based on nearest neighbor is used. Furthermore, by using a defined fitness function in this paper, the... 

ILS-based reservoir is a bio-inspired computational model consisting of spiking neurons which has been designed to process spatiotemporal patterns appropriately. In ILS-based reservoir, the neurons are located in an ionic environment and the connections are provided by ionic density. By using ionic diffusion as a processing operation, this model is able to consider the effects of both the preceding and current stimuli properly. Since character recognition is an important task in various applications, this paper focuses on the classification of handwritten digits using ILS-based reservoir. For this purpose, a neuromorphic handwritten digit dataset called N-MNIST dataset is used as a... 

This paper focuses on localizing acoustic source using fuzzy logic. For this purpose, an array of microphones are used as sensors. The Time Delay Estimation (TDE) is performed by correlation between received signals from each pair of microphones. In this paper, instead of assuming a crisp value as a TDOA, we introduce fuzzy number of TDOA in which the absolute value of the cross correlation function is normalized and then assumed as TDOA membership function for each pair of microphones. Truth value of presenting acoustic source is computed in region of interest based on achieved TDOA membership functions. Computing this truth value is represented in this paper based on fuzzy logic. The... 

This paper proposes a fusion-based gender recognition method which uses facial images as input. Firstly, this paper utilizes pre-processing and a landmark detection method in order to find the important landmarks of faces. Thereafter, four different frameworks are proposed which are inspired by state-of-the-art gender recognition systems. The first framework extracts features using Local Binary Pattern (LBP) and Principal Component Analysis (PCA) and uses back propagation neural network. The second framework uses Gabor filters, PCA, and kernel Support Vector Machine (SVM). The third framework uses lower part of faces as input and classifies them using kernel SVM. The fourth framework uses... 

Sound source localization has always been one of the most challenging subjects in different fields of engineering, one of the most important of which being tracking of flying objects. This article focuses on sound source localization using fuzzy fusion and a beamforming method. It proposes a new fuzzy-based algorithm for localizing a sound source using distributed sensor nodes. Eight low-cost sensor nodes have been constructed in this study each of which consists of a microphone array to capture sound waves. Each node is able to record audio signals synchronously on an SD card to evaluate different algorithms offline. However, the sensor nodes are designed to be able to estimate the location... 

One of the biggest struggles while working with artificial neural networks is being able to come up with models which closely match biological observations. Biological neural networks seem to capable of creating and pruning dendritic spines, leading to synapses being changed, which results in higher learning capability. The latter forms the basis of the present study in which a new ionic model for reservoir-like networks, consisting of spiking neurons, is introduced. High plasticity of this model makes learning possible with a fewer number of neurons. In order to study the effect of the applied stimulus in an ionic liquid space through time, a diffusion operator is used which somehow...