Highly Accurate Target Motion Compensation Using Entropy Function Minimization

One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Investigation of Grid Supply Harmonic Effects in Wound Rotor Induction Machines

This paper presents an in-depth investigation of the effects of several grid supply harmonic voltages on the stator currents of an example wound rotor induction machine. The observed effects of higher order grid supply harmonics are identified using a finite element time stepping transient model, as well as a time-stepping electromagnetic model. In addition, a number of analytical equations to calculate the spectral content of the stator currents are presented in the paper. The presented equations are validated through comparison with the obtained spectra predicted using the finite element and electromagnetic models. The presented study provides a better understanding of the origin of supply harmonic effects identified in the stator currents of the example wound rotor induction machine. Furthermore, the study helps to understand the effects of higher order supply harmonics on the harmonic emissions of the wound rotor induction machine.  

A Sparse Representation Speech Denoising Method Based on Adapted Stopping Residue Error

A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure.

EEG Analysis of Brain Dynamics in Children with Language Disorders

Current study established for EEG signal analysis in patients with language disorder. Language disorder can be defined as meaningful delay in the use or understanding of spoken or written language. The disorder can include the content or meaning of language, its form, or its use. Here we applied Z-score, power spectrum, and coherence methods to discriminate the language disorder data from healthy ones. Power spectrum of each channel in alpha, beta, gamma, delta, and theta frequency bands was measured. In addition, intra hemispheric Z-score obtained by scoring algorithm. Obtained results showed high Z-score and power spectrum in posterior regions. Therefore, we can conclude that peoples with language disorder have high brain activity in frontal region of brain in comparison with healthy peoples. Results showed that high coherence correlates with irregularities in the ERP and is often found during complex task, whereas low coherence is often found in pathological conditions. The results of the Z-score analysis of the brain dynamics showed higher Z-score peak frequency in delta, theta and beta sub bands of Language Disorder patients. In this analysis there were activity signs in both hemispheres and the left-dominant hemisphere was more active than the right.

Symbolic Analysis of Power Spectrum of CMOS Cross Couple Oscillator

This paper proposes for the first time symbolic formula of the power spectrum of CMOS Cross Couple Oscillator and its modified circuit. Many principles existed to derived power spectrum in microwave textbook such as impedance, admittance parameters, ABCD, H parameters, etc. It can be compared by graph of power spectrum which methodology is the best from the point of view of practical measurement setup such as condition of impedance parameter which used superposition of current to derived (its current injection at the other port of the circuit is zero, which is impossible in reality). Four graphs of impedance parameters of cross couple oscillator are proposed. After that four graphs of scattering parameters of CMOS cross coupled oscillator will be shown.

Human Walking Vertical Force and Vertical Vibration of Pedestrian Bridge Induced by Its Higher Components

The purpose of this study is to identify human walking vertical force by using FFT power spectrum density from the experimental acceleration data of the human body. An experiment on human walking is carried out on a stationary floor especially paying attention to higher components of dynamic vertical walking force. Based on measured acceleration data of the human lumbar part, not only in-phase component with frequency of 2fw, 3fw, but also in-opposite-phase component with frequency of 0.5 fw, 1.5 fw, 2.5 fw where fw is the walking rate is observed. The vertical vibration of pedestrian bridge induced by higher components of human walking vertical force is also discussed in this paper. A full scale measurement for the existing pedestrian bridge with center span length of 33 m is carried out focusing on the resonance phenomenon due to higher components of human walking vertical force. Dynamic response characteristics excited by these vertical higher components of human walking are revealed from the dynamic design viewpoint of pedestrian bridge.

Unsupervised Classification of DNA Barcodes Species Using Multi-Library Wavelet Networks

DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

In situ Modelling of Lateral-Torsional Vibration of a Rotor-Stator with Multiple Parametric Excitations

This paper presents a 4-DOF nonlinear model of a cracked de Laval rotor-stator system derived based on Energy Principles. The model has been used to simulate coupled torsionallateral response of the faulty system with multiple parametric excitations; rotor-stator-rub, a breathing transverse crack, eccentric mass and an axial force. Nonlinearity of a “breathing” crack is incorporated in the model using a simple hinge mechanism suitable for a shallow crack. Response of the system while passing via its critical speed with intermittent rotor-stator rub is analyzed. Effects of eccentricity with phase and acceleration are investigated. Features of crack, rub and eccentricity in vibration response are explored for condition monitoring. The presence of a crack and rub are observable in the power spectrum despite excitations by an axial force and rotor unbalance. Obtained results are consistent with existing literature and could be adopted into rotor condition monitoring strategies.

Dynamics and Control of a Chaotic Electromagnetic System

In this paper, different nonlinear dynamics analysis techniques are employed to unveil the rich nonlinear phenomena of the electromagnetic system. In particular, bifurcation diagrams, time responses, phase portraits, Poincare maps, power spectrum analysis, and the construction of basins of attraction are all powerful and effective tools for nonlinear dynamics problems. We also employ the method of Lyapunov exponents to show the occurrence of chaotic motion and to verify those numerical simulation results. Finally, two cases of a chaotic electromagnetic system being effectively controlled by a reference signal or being synchronized to another nonlinear electromagnetic system are presented.

Development of Position Changing System for Obstructive Sleep Apnea Patient using HRV

Obstructive sleep apnea in patients, between 70 and 80 percent, can be cured with just a posture correcting. The most import thing to do this is detection of obstructive sleep apnea. Detection of obstructive sleep apnea can be performed through heart rate variability analysis using power spectrum density analysis. After HRV analysis we needed to know the current position information for correcting the position. The pressure sensors of the array type were used to obtain position information. These sensors can obtain information from the experimenter about position. In addition, air cylinder corrected the position of the experimenter by lifting the bed. The experimenter can be changed position without breaking during sleep by the system. Polysomnograph recording were obtained from 10 patients. The results of HRV analysis were that NLF and LF/HF ratio increased, while NHF decreased during OSA. Position change had to be done the periods.

Vector Space of the Extended Base-triplets over the Galois Field of five DNA Bases Alphabet

A plausible architecture of an ancient genetic code is derived from an extended base triplet vector space over the Galois field of the extended base alphabet {D, G, A, U, C}, where the letter D represent one or more hypothetical bases with unspecific pairing. We hypothesized that the high degeneration of a primeval genetic code with five bases and the gradual origin and improvements of a primitive DNA repair system could make possible the transition from the ancient to the modern genetic code. Our results suggest that the Watson-Crick base pairing and the non-specific base pairing of the hypothetical ancestral base D used to define the sum and product operations are enough features to determine the coding constraints of the primeval and the modern genetic code, as well as the transition from the former to the later. Geometrical and algebraic properties of this vector space reveal that the present codon assignment of the standard genetic code could be induced from a primeval codon assignment. Besides, the Fourier spectrum of the extended DNA genome sequences derived from the multiple sequence alignment suggests that the called period-3 property of the present coding DNA sequences could also exist in the ancient coding DNA sequences.

Noise Estimation for Speech Enhancement in Non-Stationary Environments-A New Method

This paper presents a new method for estimating the nonstationary noise power spectral density given a noisy signal. The method is based on averaging the noisy speech power spectrum using time and frequency dependent smoothing factors. These factors are adjusted based on signal-presence probability in individual frequency bins. Signal presence is determined by computing the ratio of the noisy speech power spectrum to its local minimum, which is updated continuously by averaging past values of the noisy speech power spectra with a look-ahead factor. This method adapts very quickly to highly non-stationary noise environments. The proposed method achieves significant improvements over a system that uses voice activity detector (VAD) in noise estimation.

Wavelet Enhanced CCA for Minimization of Ocular and Muscle Artifacts in EEG

Electroencephalogram (EEG) recordings are often contaminated with ocular and muscle artifacts. In this paper, the canonical correlation analysis (CCA) is used as blind source separation (BSS) technique (BSS-CCA) to decompose the artifact contaminated EEG into component signals. We combine the BSSCCA technique with wavelet filtering approach for minimizing both ocular and muscle artifacts simultaneously, and refer the proposed method as wavelet enhanced BSS-CCA. In this approach, after careful visual inspection, the muscle artifact components are discarded and ocular artifact components are subjected to wavelet filtering to retain high frequency cerebral information, and then clean EEG is reconstructed. The performance of the proposed wavelet enhanced BSS-CCA method is tested on real EEG recordings contaminated with ocular and muscle artifacts, for which power spectral density is used as a quantitative measure. Our results suggest that the proposed hybrid approach minimizes ocular and muscle artifacts effectively, minimally affecting underlying cerebral activity in EEG recordings.

Development for the Evaluation Index of an Anesthesia Depth using the Bispectrum Analysis

The linear SEF (Spectral Edge Frequency) parameter and spectrum analysis method can not reflect the non-linear of EEG. This method can not contribute to acquire real time analysis and obtain a high confidence in the clinic due to low discrimination. To solve the problems, the development of a new index is carried out using the bispectrum analyzing the EEG(electroencephalogram) including the non-linear characteristic. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. New index could afford to effectively discriminate the awake and anesthesia state.

Fractal Analysis on Human Colonic Pressure Activities based on the Box-counting Method

The colonic tissue is a complicated dynamic system and the colonic activities it generates are composed of irregular segmental waves, which are referred to as erratic fluctuations or spikes. They are also highly irregular with subunit fractal structure. The traditional time-frequency domain statistics like the averaged amplitude, the motility index and the power spectrum, etc. are insufficient to describe such fluctuations. Thus the fractal box-counting dimension is proposed and the fractal scaling behaviors of the human colonic pressure activities under the physiological conditions are studied. It is shown that the dimension of the resting activity is smaller than that of the normal one, whereas the clipped version, which corresponds to the activity of the constipation patient, shows with higher fractal dimension. It may indicate a practical application to assess the colonic motility, which is often indicated by the colonic pressure activity.

Vibration Induced Fatigue Assessment in Vehicle Development Process

Improvement in CAE methods has an important role for shortening of the vehicle product development time. It is provided that validation of the design and improvements in terms of durability can be done without hardware prototype production. In recent years, several different methods have been developed in order to investigate fatigue damage of the vehicle. The intended goal among these methods is prediction of fatigue damage in a short time with reduced costs. This study developed a new fatigue damage prediction method in the automotive sector using power spectrum densities of accelerations. This study also confirmed that the weak region in vehicle can be easily detected with the method developed in this study which results were compared with conventional method.

Improved Power Spectrum Estimation for RR-Interval Time Series

The RR interval series is non-stationary and unevenly spaced in time. For estimating its power spectral density (PSD) using traditional techniques like FFT, require resampling at uniform intervals. The researchers have used different interpolation techniques as resampling methods. All these resampling methods introduce the low pass filtering effect in the power spectrum. The lomb transform is a means of obtaining PSD estimates directly from irregularly sampled RR interval series, thus avoiding resampling. In this work, the superiority of Lomb transform method has been established over FFT based approach, after applying linear and cubicspline interpolation as resampling methods, in terms of reproduction of exact frequency locations as well as the relative magnitudes of each spectral component.

Comparison of the Parameter using ECG with Bisepctrum Parameter using EEG during General Anesthesia

The measurement of anesthetic depth is necessary in anesthesiology. NN10 is very simple method among the RR intervals analysis methods. NN10 parameter means the numbers of above the 10 ms intervals of the normal to normal RR intervals. Bispectrum analysis is defined as 2D FFT. EEG signal reflected the non-linear peristalsis phenomena according to the change brain function. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. In this paper, the relation between NN10 parameter using ECG and bisepctrum index using EEG is observed to estimate the depth of anesthesia during anesthesia and then we estimated the utility of the anesthetic.

A New Secure Communication Model Based on Synchronization of Coupled Multidelay Feedback Systems

Recent research result has shown that two multidelay feedback systems can synchronize each other under different schemes, i.e. lag, projective-lag, anticipating, or projectiveanticipating synchronization. There, the driving signal is significantly complex due that it is constituted by multiple nonlinear transformations of delayed state variable. In this paper, a secure communication model is proposed based on synchronization of coupled multidelay feedback systems, in which the plain signal is mixed with a complex signal at the transmitter side and it is precisely retrieved at the receiver side. The effectiveness of the proposed model is demonstrated and verified in the specific example, where the message signal is masked directly by the complex signal and security is examined under the breaking method of power spectrum analysis.