Structural Study of Boron - Nitride Nanotube with Magnetic Resonance (NMR) Parameters Calculation via Density Functional Theory Method (DFT)

A model of (4, 4) single-walled boron-nitride nanotube as a representative of armchair boron-nitride nanotubes studied. At first the structure optimization performed and then Nuclear Magnetic Resonance parameters (NMR) by Density Functional Theory (DFT) method at 11B and 15N nuclei calculated. Resulted parameters evaluation presents electrostatic environment heterogeneity along the nanotube and especially at the ends but the nuclei in a layer feel the same electrostatic environment. All of calculations carried out using Gaussian 98 Software package.

Recursive Wiener-Khintchine Theorem

Power Spectral Density (PSD) computed by taking the Fourier transform of auto-correlation functions (Wiener-Khintchine Theorem) gives better result, in case of noisy data, as compared to the Periodogram approach. However, the computational complexity of Wiener-Khintchine approach is more than that of the Periodogram approach. For the computation of short time Fourier transform (STFT), this problem becomes even more prominent where computation of PSD is required after every shift in the window under analysis. In this paper, recursive version of the Wiener-Khintchine theorem has been derived by using the sliding DFT approach meant for computation of STFT. The computational complexity of the proposed recursive Wiener-Khintchine algorithm, for a window size of N, is O(N).

Density Functional Calculations of N-14 andB-11 NQR Parameters in the H-capped (5, 5)Single-Wall BN Nanotube

Density functional theory (DFT) calculations were performed to compute nitrogen-14 and boron-11 nuclear quadrupole resonance (NQR) spectroscopy parameters in the representative model of armchair boron nitride nanotube (BNNT) for the first time. The considered model consisting of 1 nm length of H-capped (5, 5) single-wall BNNT were first allowed to fully relax and then the NQR calculations were carried out on the geometrically optimized model. The evaluated nuclear quadrupole coupling constants and asymmetry parameters for the mentioned nuclei reveal that the model can be divided into seven layers of nuclei with an equivalent electrostatic environment where those nuclei at the ends of tubes have a very strong electrostatic environment compared to the other nuclei along the length of tubes. The calculations were performed via Gaussian 98 package of program.

A Robust Extrapolation Method for Curtailed Aperture Reconstruction in Acoustic Imaging

Acoustic Imaging based sound localization using microphone array is a challenging task in digital-signal processing. Discrete Fourier transform (DFT) based near-field acoustical holography (NAH) is an important acoustical technique for sound source localization and provide an efficient solution to the ill-posed problem. However, in practice, due to the usage of small curtailed aperture and its consequence of significant spectral leakage, the DFT could not reconstruct the active-region-of-sound (AROS) effectively, especially near the edges of aperture. In this paper, we emphasize the fundamental problems of DFT-based NAH, provide a solution to spectral leakage effect by the extrapolation based on linear predictive coding and 2D Tukey windowing. This approach has been tested to localize the single and multi-point sound sources. We observe that incorporating extrapolation technique increases the spatial resolution, localization accuracy and reduces spectral leakage when small curtail aperture with a lower number of sensors accounts.

An Improved ICI Self-Cancellation Scheme for Multi-Carrier Communication Systems

For broadband wireless mobile communication systems the orthogonal frequency division multiplexing (OFDM) is a suitable modulation scheme. The frequency offset between transmitter and receiver local oscillator is main drawback of OFDM systems, which causes intercarrier interference (ICI) in the subcarriers of the OFDM system. This ICI degrades the bit error rate (BER) performance of the system. In this paper an improved self-ICI cancellation scheme is proposed to improve the system performance. The proposed scheme is based on discrete Fourier transform-inverse discrete Fourier transform (DFT-IDFT). The simulation results show that there is satisfactory improvement in the bit error rate (BER) performance of the present scheme.

Speaker Identification using Neural Networks

The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.

Estimating Frequency, Amplitude and Phase of Two Sinusoids with Very Close Frequencies

This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.

Investigation on Metalosalen Complexes Binding to DNA using Ab Initio Calculations

Geometry optimizations of metal complexes of Salen(bis(Salicylidene)1,2-ethylenediamine) were carried out at HF and DFT methods employing Lanl2DZ basis set. In this work structural, energies, bond lengths and other physical properties between Mn2+,Cu2+ and Ni2+ ions coordinated by salen–type ligands are examined. All calculations were performed using Gaussian 98W program series. To investigate local aromaticities, NICS were calculated at all centers of rings. The higher the band gap indicating a higher global aromaticity. The possible binding energies have been evaluated. We have evaluated Frequencies and Zero-point energy with freq calculation. The NICS(Nucleous Independent Chemical Shift) Results show Ni(II) complexes are antiaromatic and aromaticites of Mn(II) complexes are larger than Cu(II) complexes. The energy Results show Cu(II) complexes are stability than Mn(II) and Ni(II) complexes.

Video Quality assessment Measure with a Neural Network

In this paper, we present the video quality measure estimation via a neural network. This latter predicts MOS (mean opinion score) by providing height parameters extracted from original and coded videos. The eight parameters that are used are: the average of DFT differences, the standard deviation of DFT differences, the average of DCT differences, the standard deviation of DCT differences, the variance of energy of color, the luminance Y, the chrominance U and the chrominance V. We chose Euclidean Distance to make comparison between the calculated and estimated output.

Computational Studies of Binding Energies and Structures of Methylamine on Functionalized Activated Carbon Surfaces

Empirical force fields and density functional theory (DFT) was used to study the binding energies and structures of methylamine on the surface of activated carbons (ACs). This is a first step in studying the adsorption of alkyl amines on the surface of functionalized ACs. The force fields used were Dreiding (DFF), Universal (UFF) and Compass (CFF) models. The generalized gradient approximation with Perdew Wang 91 (PW91) functional was used for DFT calculations. In addition to obtaining the aminecarboxylic acid adsorption energies, the results were used to establish reliability of the empirical models for these systems. CFF predicted a binding energy of -9.227 (kcal/mol) which agreed with PW91 at - 13.17 (kcal/mol), compared to DFF 0 (kcal/mol) and UFF -0.72 (kcal/mol). However, the CFF binding energies for the amine to ester and ketone disagreed with PW91 results. The structures obtained from all models agreed with PW91 results.

Influences of Si and C- Doping on the Al-27 and N-14 Quardrupole Coupling Constants in AlN Nanotubes: A DFT Study

A computational study at the level density functional theory (DFT) was carried out to investigate the influences of Si and C-doping on the 14N and 27Al quadrupole coupling constant in the (10, 0) zigzag single ? walled Aluminum-Nitride nanotube (AlNNT). To this aim, a 1.16nm, length of AlNNT consisting of 40 Al atoms and 40 N atoms were selected where the end atoms are capped by hydrogen atom. To follow the purpose, three Si atoms and three C atoms were doped instead of three Al atoms and three N atoms as a central ring in the surface of the Si and C-doped AlNNT. At first both of systems optimized at the level of BLYP method and 6-31G (d) basis set and after that, the NQR parameters were calculated at the level BLYP method and 6-311+G** basis set in two optimized forms. The calculate CQ values for both optimized AlNNT systems, raw and Si and C-doped, reveal different electronic environments in the mentioned systems. It was also demonstrated that the end nuclei have the largest CQ values in both considered AlNNT systems. All the calculations were carried out using Gaussian 98 package of program.

A Novel FFT-Based Frequency Offset Estimator for OFDM Systems

This paper proposes a novel frequency offset (FO) estimator for orthogonal frequency division multiplexing. Simplicity is most significant feature of this algorithm and can be repeated to achieve acceptable accuracy. Also fractional and integer part of FO is estimated jointly with use of the same algorithm. To do so, instead of using conventional algorithms that usually use correlation function, we use DFT of received signal. Therefore, complexity will be reduced and we can do synchronization procedure by the same hardware that is used to demodulate OFDM symbol. Finally, computer simulation shows that the accuracy of this method is better than other conventional methods.

Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.