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Journal Cover Advances in Signal Processing
  [11 followers]  Follow
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2332-6883 - ISSN (Online) 2332-6891
   Published by Horizon Research Publishing Homepage  [54 journals]
  • Design and Analysis of a Quantum Circuit to Cluster a Set of Data Points

    • Abstract: Publication date:  Oct 2016
      Source:Advances in Signal Processing  Volume  4  Number  2  Sanjay Chakraborty   Sambit Halder   and Shamik Kundu   Clustering is a powerful tool which has been used in several applications (such as, fraud detection, pattern matching etc.). It is known to all that quantum counterpart is more superior to classical one on some specific areas. Quantum computation can solve certain problems much faster than classical computation. This paper mainly proposes a quantum circuit to cluster a given set of points with respect to pre-defined points. It uses binary quantum logic and superpositions principle of quantum mechanics. This proposed approach is a collaboration of data mining techniques with quantum computation. Very few works have been done in this area. In this paper, some of the previous works are also analyzed on the idea of applying quantum concept to the classical approach of clustering algorithms.
      PubDate: Oct 2016
  • Increasing the Accuracy of Reverberation Time Measurement Using Wavelet

    • Abstract: Publication date:  Apr 2016
      Source:Advances in Signal Processing  Volume  4  Number  1  Denny Hermawato   and Hastuadi Harsa   Reverberation time measurement is used in building acoustic analysis and determination of acoustic characteristic of a material such as sound transmission loss and sound absorption index. This process measures the time needed for sound to decay 60 dB since the steady sound in the room is switched off. Usually, the reverberation time is estimated from sound decay curve. In the real reverberation time measurement, the smooth sound decay curve is hard to find because the original sound wave combines with reflection sound wave. In this paper, two level Daubechies wavelet transform is performed to filter noise in the sound decay. The applied wavelet thresholding successfully filtered out the maximum and minimum peak in the sound decay curve, therefore the estimation of reverberation time can be done more accurately in high and low frequency region.
      PubDate: Apr 2016
  • Utilization of Encoding Techniques at the Signal Transmission in the
           Optical Fiber

    • Abstract: Publication date:  May 2015
      Source:Advances in Signal Processing  Volume  3  Number  2  Filip Certik   This paper presents a possible utilization of advances signal processing techniques in the optical transmission system at the signal transmission. A contribution briefly introduces basic characteristics of the optical fiber, Forward Error Correction techniques and digital modulation formats considered for analysis. The paper mainly focuses on RS and BCH codes used in conjunction with OOK and BPSK techniques and their practical exploitation in the optical transmission system. Then, a created simulation program for the optical transmission system is presented with detailed description of blocks related to mutual cooperation RS and BCH codes with binary modulation techniques (OOK, DBPSK and BPSK). In the third part, more detailed analyses of RS and BCH performances are presented.
      PubDate: May 2015
  • Respiration and Heart Rate Monitoring from Photoplethysmograph Signal

    • Abstract: Publication date:  Feb 2015
      Source:Advances in Signal Processing  Volume  3  Number  1  Kiran Balaji PS   and Anand Jatti   Photoplethysmograph is a simple and cost effective method to assess cardiovascular related parameters such as heart rate, arterial blood oxygen saturation, BP the fact that the Photoplethysmograph (PPG) signal caries respiratory information. Earlier physicians used to insert separate sensors to assess respiration and heart rate. In this present work, an efficient algorithm is presented, based on the wavelet decomposition technique to extract the respiratory activity from the PPG signals. With this aim displaying of heart rate and the extraction of respiratory activity is done. Here MATLAB and MULTISIM tools were used for simulation. Wavelet decomposition performed exceptionally well for extraction of respiratory activity from PPG. Extracted signal is compared with a signal which was acquired from the existing respiratory sensor and the correlation between them is up to 90%. Then the obtained parameters are sent to the physician's mobile phone for faster and better assessment of the patient from remote places. Hence using this method it can reduce the usage of sensor for respiration, and also reduces the discomfort caused to the patient, also cost effective.
      PubDate: Feb 2015
  • Duobinary Modulation Format in Optical Communication Systems

    • Abstract: Publication date:  Feb 2015
      Source:Advances in Signal Processing  Volume  3  Number  1  Pavol Šalík   Filip Čertík   and Rastislav Róka   This paper presents the environment of the optical fiber and digital information transmission over optical fiber, using signal transformation technique called duobinary modulation technique. We propose a complete duobinary encoder and duobinary decoder that we tested in Matlab simulink R2014B. In the final part, it will be shown a comparison of duobinary modulation technique with on-off keying modulation technique
      PubDate: Feb 2015
  • System Determining Pronunciation Correctness of Japanese Words

    • Abstract: Publication date:  Oct 2014
      Source:Advances in Signal Processing  Volume  2  Number  3  Z. Syroka   P. Dubiowicz   and T. Zajac   A system determining pronunciation correctness of Japanese words is presented. The system is composed of six separate modules: signal segmentation, transcription interpretation, synthesis, comparison, error interpretation and phonetic database. The system uses two input sources: speech signal and its Latin transcription. The system is designed to deal specifically with Japanese language, due to the language's specificity in terms of speech. Based on the input, a timeline pointing out the locations of vowels is calculated, followed by determining the locations of all the moras (syllable timings). The signal, segmented in such a way, is then compared with a signal synthesized using a phonetic database and the transcription data. As a result the differences are pointed out and interpreted.
      PubDate: Oct 2014
  • Dictionary Learning for Scalable Sparse Image Representation with

    • Abstract: Publication date:  Mar 2014
      Source:Advances in Signal Processing  Volume  2  Number  2  Bojana Begovic   Vladimir Stankovic   and Lina Stankovic   This paper introduces a novel design for the dictionary learning algorithm, intended for scalable sparse representation of high motion video sequences and natural images. The proposed algorithm is built upon the foundation of the K-SVD framework originally designed to learn non-scalable dictionaries for natural images. Proposed design is mainly motivated by the main perception characteristic of the Human Visual System (HVS) mechanism. Specifically, its core structure relies on the exploitation of the high-frequency image components and contrast variations in order to achieve visual scene objects identification at all scalable levels. Proposed design is implemented by introducing a semi-random Morphological Component Analysis (MCA) based initialization of the K-SVD dictionary and the regularization of its atom’s update mechanism. In general, dictionary learning for sparse representations leads to state-of-the-art image restoration results for several different problems in the field of image processing. In experimental section we show that these are equally achievable by accommodating all dictionary elements to tailor the scalable data representation and reconstruction, hence modeling data that admit sparse representation in a novel manner. Performed simulations include scalable sparse recovery for representation of static and dynamic data changing over time (e.g., video) together with application to denoising and compressive sensing.
      PubDate: Mar 2014
  • Solution of Problem of Sound Scattering on Bodies of Non-analytical Form
           with Help of Method of Green’s Functions

    • Abstract: Publication date:  Mar 2014
      Source:Advances in Signal Processing  Volume  2  Number  2  S. L. Ilmenkov   and A. A. Kleshchev   The real scatterers have non – analytical form and therefore, the method of separation of variables for calculation of the reflected sound field does not apply to them. In the article is presented the method of Green’s functions for the solution of the problem of the sound diffraction on the ideal non – analytical scatterers. In detail is giving the analysis of the solutions and are calculating the modules of the angular characteristics of the sound scattering.
      PubDate: Mar 2014
  • Diffraction of Sound Signals at Elastic Shell of Non-analytical Form Put
           in Plane Waveguide

    • Abstract: Publication date:  Mar 2014
      Source:Advances in Signal Processing  Volume  2  Number  2  A. Kleshchev   With the help of the method of imaginary sources and imaginary scatterers, of the method of integral equations and of the Fourier transform is solved the problem of the diffraction of the pulse sound signal at elastic body of the non-analytical form, put in the plane waveguide.
      PubDate: Mar 2014
  • Acoustical Imaging in Heterogeneous Environments

    • Abstract: Publication date:  Mar 2014
      Source:Advances in Signal Processing  Volume  2  Number  2  Victor D. Svet   This review describes methods of reconstruction of acoustic images of objects located in heterogeneous environments. These methods can be divided into two groups: linear methods (the matched filtering and time reversed acoustics) and non-linear methods of speckle holography and speckle interferometry, which began to develop rapidly in recent years as alternative to linear methods.
      PubDate: Mar 2014
  • Can the Threshold Performance of Maximum Likelihood DOA Estimation be
           Improved by Tools from Random Matrix Theory?

    • Abstract: Publication date:  Jan 2014
      Source:Advances in Signal Processing  Volume  2  Number  1  Yuri I. Abramovich   and Ben A. Johnson   For direction of arrival (DOA) estimation in the threshold region, it has been shown that use of Random Matrix Theory (RMT) eigensubspace estimates provides significant improvement in MUSIC performance. Here we investigate whether these RMT methods can also improve the threshold performance of unconditional (stochastic) maximum likelihood DOA estimation (MLE).
      PubDate: Jan 2014
  • Ultrasound Flow Imaging through Thick Skull Bones in Spaced "Transmitter &
           Receiver" Mode

    • Abstract: Publication date:  Jan 2014
      Source:Advances in Signal Processing  Volume  2  Number  1  V.D.Svet   T.V.Kondratieva   N.V. Zuikova   and S.V. Baykov   Some simulation and experimental results of ultrasonic speckle imaging of blood flow in the brain vessels through the thick bones of skull are discussed. The method of imaging previously described in [1] is based on non-linear speckle interferometric processing of echoes scattered by formed elements of the blood. It is shown that the standard combined scheme “transmitter – receiver” significantly inferior to the scheme of spaced “receiver – transmitter” where the effects of multiple reflections from the boundaries of the bones are considerably minimized, and that improves the output signal/noise ratio and the image contrast. The experimental results of visualization of blood flow, using standard Doppler method and speckle processing are presented.
      PubDate: Jan 2014
  • Out-of-Band Emission Reduction Technique for OFDM and MC-CDMA Systems

    • Abstract: Publication date:  Jan 2014
      Source:Advances in Signal Processing  Volume  2  Number  1  Igor Gepko   In this paper, we introduce a method for out-of-band power reduction of multicarrier communication systems. Recent years MC systems possess a dominated role in wireless access due to ability to achieve high data rates and simultaneously high robustness to multipath and fading. Despite all advantages, MC transmission produces an essential out-of-band interference. The OOB radiation leads to the wastage of scarce spectral resources and severe threats to adjacent wireless channels. We propose a novel technique for reducing OOB radiations in OFDM and MC-CDMA systems. To reduce the OOB emissions in the MC-CDMA system, we propose analytical criterion for spectrum efficiency estimation as far as low complexity algebraic algorithm for the proper waveform selection. The structure of selected waveform provides suppression for radiation outside the signal necessary bandwidth. Being implemented in the OFDM system, proposed algorithm is used for calculation of phases of cancellation carriers suppressing most powerful OOB sidelobesin transmitted signal. In the final part of document we consider primer of the simple precoding procedure for OFDM systems which by 10 dB or more reduces the OOB power at the cost of inessential decrease of the information data rate.
      PubDate: Jan 2014
  • Time-sequential Speaker Recognition System

    • Abstract: Publication date:  Dec 2014
      Source:Advances in Signal Processing  Volume  2  Number  4  Syroka Zenon   Tomasz Zając   Paweł Dubiłowicz   and Cezary Łabarzewski   The method presented in this publication was submitted in a patent application in May 2011, the patent was granted on December 17, 2014. It is a continuation of speech signal recognition study [1] carried out at the UWM. In 2010 a "Speech analysis and recognition method and system" [2] has been developed using sequential analysis basing on the Walsh basis functions. The present system includes time-variability of the speech signal spectrum. Basic block diagrams describing the system's mechanics have been presented.
      PubDate: Dec 2014
  • Decomposition of Complex Signal on Lorenz Components

    • Abstract: Publication date:  Sep 2013
      Source:Advances in Signal Processing  Volume  1  Number  2  Natalia Shcherbakova Algorithm of complex signal decomposition on elementary components having Lorenz form is proposed. The non-linear minimization problem to the problem of linear equation solving. The number of components is the necessary aprioir information. The algorithm can be combined with the method of statistical regularization. The results of numerical experiments are represented.
      PubDate: Sep 2013
  • Comparison of Artificial Intelligence Methods on the Example of Tea
           Classification Based on Signals from E-nose Sensors

    • Abstract: Publication date:  Sep 2013
      Source:Advances in Signal Processing  Volume  1  Number  2  Pawel Plawiak and Wojciech Maziarz The data collected from electronic nose systems are multidimensional and usually contain a lot of redundant information. In order to extract only the relevant data, different computational techniques are developed. The article presents and compares selected pattern recognition algorithms in application to qualitative determination of different brands of tea. The measured responses of an array of 18 semiconductor gas sensors formed input vectors used for further analysis. The initial data processing consisted on standardization, principal component analysis, data normalization and reduction. Soft computing one can divide into single method systems using neural networks, fuzzy systems, and hybrid systems like evolutionary-neural, neuro-fuzzy, evolutionary-fuzzy. All the presented systems were evaluated based on accuracy (generated error) and complexity (number of parameters and training time) criteria. A novel method of forming input data vector by aggregation of the first three principal components is also presented.
      PubDate: Sep 2013
  • Interference of Impulses, Scattered and Radiated by Bodies of Spheroidal

    • Abstract: Publication date:  Sep 2013
      Source:Advances in Signal Processing  Volume  1  Number  2  Alexander Kleshchev With the help of the Fourier transform and characteristics of the scattering of the stationary (continuous) sound signal are calculated the interference of the impulses, scattered and radiated by bodies of the prolate spheroidal form (ideal and elastic), with the harmonic and the frequency-modulated filling.
      PubDate: Sep 2013
  • Event Reconstruction by Digital Filtering

    • Abstract: Publication date:  Nov 2013
      Source:Advances in Signal Processing  Volume  1  Number  3  Olugboji Oluwafemi Ayodeji   Jonathan Yisa Jiya   and Jack M. Hale   This work deals with a digital filtering technique that was developed to reconstruct a pulse after it has propagated along a pipe; a complex pulse that is progressively distorted. The technique developed makes use of the theory of digital filtering used in communications to remove distortion in long telephone links.
      PubDate: Nov 2013
  • Against Phase Veloсities of Elastic Waves in Thin Orthotropic
           Cylindrical Shell

    • Abstract: Publication date:  Nov 2013
      Source:Advances in Signal Processing  Volume  1  Number  3  A.A. Kleshchev   In paper is received the characteristic equation for the determine of wave numbers of phase velocities of elastic waves in the thin cylindrical shell with the help of the dynamic theory of the elasticity for the orthotropic medium and of the hypothesis of thin shells.
      PubDate: Nov 2013
  • A Novel Floating Point Fast Confluence Adaptive Independent Component
           Analysis for Signal Processing Applications

    • Abstract: Publication date:  Nov 2013
      Source:Advances in Signal Processing  Volume  1  Number  3  Jayasanthi Ranjith. M.E.   and Dr.NJR.Muniraj   Independent component analysis (ICA) is a technique that separates the independent source signals from their mixtures by minimizing the statistical dependence between components. This paper presents a floating point implementation of a novel fast confluence adaptive independent component analysis (FCAICA) technique with reduced number of iterations that provides the high convergence speed. Fixed point ICA algorithms cover only smaller range of numbers. To handle large as well as tiny numbers and hence to improve the dynamic range of the signal values, floating point operations are performed in ICA. The high convergence speed is achieved by a novel optimization scheme that adaptively changes the weight vector based on the kurtosis value. To validate the performance of the proposed FCAICA, simulation and synthesis are performed with super-gaussian mixtures and sub Gaussian mixtures and experimental results provided. The proposed FCAICA processor separates the super-Gaussian signals with a maximum operating frequency of 2.91MHz with improved convergence speed.
      PubDate: Nov 2013
  • Scattering of Pulse Sound Signals on Elastic Body

    • Abstract: Publication date:  Jul 2013
      Source:Advances in Signal Processing  Volume  1  Number  1  A. A. Kleshchev With the help of the Fourier transform and of the method of the imaginary sources and imaginary scatterers is solved the problem of the scattering of the pulse sound signal by the elastic spheroidal shell, put in the plane waveguide.
      PubDate: Jul 2013
  • Signal Processing with Regularized Multistep Support Vector Method

    • Abstract: Publication date:  Jul 2013
      Source:Advances in Signal Processing  Volume  1  Number  1  Valery R. Fazylov and Nathalie K. Shcherbakova A new method is proposed for processing the signal distorted by random noise. The processing model is based on a statistical regularization method, and the obtained system of linear equations and inequalities is solved using a multistep support vector method. An advantage of this approach is that the iterative nature of the algorithm makes it possible to take into account the a priori information on the solution represented by the inequalities. The results of numerical experiments showing the efficiency of the algorithm are given.
      PubDate: Jul 2013
  • Diffraction of Sound Impulses on Isotropic Bodies of Spherical Form
           (Strict Solution)

    • Abstract: Publication date:  Dec 2013
      Source:Advances in Signal Processing  Volume  1  Number  4  A. A. Kleshchev   and A. S. Klimenkov   In the scientific paper are submitted the calculations of form and duration of sound impulses with the harmonic infill, scattered from elastic spherical shell and elastic isotropic sphere, made with the use of dynamic theory of elasticity.
      PubDate: Dec 2013
  • Evaluation of Associated Motion Parameters of Descending Moon Impact Probe
           (MIP) of Chandrayan-1 from Time Sequential Images

    • Abstract: Publication date:  Dec 2013
      Source:Advances in Signal Processing  Volume  1  Number  4  Vinay K Srivastava   Tapas Kumar Nandy   and Anurag Verma   The MIP, a micro satellite probe onboard Chandrayaan -1 was designed to impact on moon surface at pre decided location for scientific data collection from close range which was released from Chandrayaan-1 mother ship on 14th November 2008. This MIP impacted near the moon surface near south-pole after 24 minutes from its release and while descending MIP suffered a composite motions consisting of three fundamental motions viz. spinning, coning and forward translational (velocity). Such descending MIP showed a definite pattern of coverage on moon surface. Therefore in order to monitor and to select future landing site of impact on moon surface the associated component of motion viz.; spinning rate, coning rate, velocity of descend of MIP needs to be calculated and known. In view of this, an attempt has been made here to derive associated parameters of composite motions and attitude of MIP for predicting future impact site of descending probe on moon surface from the orbiting space craft using the time sequential images acquired by the descending MIP and the algorithm developed under MATLAB after Srivastava et. al. 2011.
      PubDate: Dec 2013
  • Comparative Performance Analysis of Filtered-xLMS and Feedback ANC
           Adaptive Algorithms to Control the Attenuation of Acoustic Noise

    • Abstract: Publication date:  Dec 2013
      Source:Advances in Signal Processing  Volume  1  Number  4  Tushar Kanti Roy   This paper presents the comparative performance analysis of two adaptive algorithms to control the attenuation of acoustic noise. Active noise control (ANC) is one of the most popular applications for adaptive filters. The basic idea behind the active control of acoustic noise is to inject a secondary sound (anti-noise) into an environment so as to cancel the primary sound using destructive interference. So, ANC is a method of reducing the unwanted noise by actively generating an anti-noise, cancelling out the noise. To achieve this objective, throughout this paper, I describe two well-known filtered-x least Mean Square (filtered-x LMS) and feedback active noise control algorithms which provide a new structure for improving acoustic noise reduction. Finally, from the simulation results, it is obvious that the proposed adaptive algorithms can effectively control the acoustic narrowband noise from the corrupted speech signal.
      PubDate: Dec 2013
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