Articles
<![CDATA[Voice Activity Robust Detection of Noisy Speech in Toeplitz ]]>
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 1: January 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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<![CDATA[A Toeplitz de-noising method using the maximum eigenvalue is proposed for the voice activity detection at low SNR scenarios. This method uses the self-correlation sequence of speech bandwidth spectrum to construct a new symmetric Toeplitz matrix and to compute the largest eigenvalue, and the double decision thresholds in the largest eigenvalue are applied in the decision framewok. Simulation results show that the presented algorithm is more effective in distinguishing speech from noise and has better robustness under various noisy environments. Compared with novel method of recurrence rate analysis, this algorithm shows lower wrong decision rate. The algorithm is of low computational complexity and is simple in real-time realization． DOI: http://dx.doi.org/10.11591/telkomnika.v13i1.6902 ]]>
<![CDATA[Two Wheeled Robot Self Balancing Control Research ]]>
<![CDATA[Ni Dan]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 3: June 2016 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v2.i3.pp617-624
<![CDATA[According to movement balancing and position control problem of Self Balancing Two Wheeled Robot, a method based on H∞ Robust Control was proposed. We apply it onto the MIMO nonlinear model of robot, and simulated it in the MATLAB environment The simulation results shows that the robot can be balanced in fixed position well by this method, and also it have the ability to anti interference.]]>
<![CDATA[A Quantum Pointer Signal Processing Research ]]>
<![CDATA[Shuyue Wu]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 2, No 3: June 2016 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v2.i3.pp675-683
<![CDATA[In quantum gray-scale image processing, the storage in quantum states is the color information and the position information According to the advantage of small range of the gray scale in a gray-scale image, a novel storage expression of quantum gray-scale image is proposed and demonstrated in this study. Besides, a new concept of "quantum pointer" is put forward based on the expression. Quantum pointer is the vinculum between the information of gray-scale and position of each pixel in quantum gray-scale images. The feasibility is verified for the proposed quantum pointer, and the properties of bi-direction and sub-block are used, the storing and other operations of quantum gray-scale image are simpler and more convenient. ]]>
<![CDATA[Random Sampling and Signal Bregman Reconstruction Based on Compressed Sensing ]]>
<![CDATA[Guojun Qin]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 2: November 2016 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v4.i2.pp365-372
<![CDATA[Compressed sensing (CS) sampling is a sampling method which is based on the signal sparse. Much information can be extracted from as little as possible of the data by applying CS and this method is the idea of great theoretical and applied prospects. In the framework of compressed sensing theory, the sampling rate is no longer decided in the bandwidth of the signal, but it depends on the structure and content of the information in the signal. In this paper, the signal is the sparse in the Fourier transform and random sparse sampling is advanced by programing random observation matrix for peak random base. The signal is successfully restored by the use of Bregman algorithm. The signal is described in the transform space, and a theoretical framework is established with a new signal descriptions and processing. By making the case to ensure that the information loss, signal is sampled at much lower than the Nyquist sampling theorem requiring rate,but also the signal is completely restored in high probability. The random sampling has following advantages: alias-free sampling frequency need not obey the Nyquist limit and higher frequency resolution.]]>
<![CDATA[A Nonlinear System of Generalized Predictive Control ]]>
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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<![CDATA[Generalized predictive control (GPC) algorithm has been applied to all kinds of industry control systems. But systemic and effective method for nonlinear system has not been found. To this problem, this paper integrates the characteristics of PID technology and GPC, present a PID generalized predictive control algorithm for a class of nonlinear system, and improves the control quality of the system. DOI: http://dx.doi.org/10.11591/telkomnika.v13i3.7215 ]]>
<![CDATA[A Compressed Sensing Signal Processing Research ]]>
<![CDATA[Guojun Qin]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 3, No 1: July 2016 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v3.i1.pp119-125
<![CDATA[The classical Shannon/Nyquist sampling theorem tells us that in order to not lose information when uniformly sampling a signal we must sample at least two times faster than its bandwidth. Nowadays in many applications, because of the restriction of the Nyquist rate, we end up with too many samples and it becomes a great challenge for further transmission and storage. In recent years, an emerging theory of signal acquirement, compressed sensing(CS), is a ground-breaking idea compared with the conventional framework of Nyquist sampling theorem. It considers the sampling in an novel way, and open up a brand new field for signal sampling process. It also reveals a promising future of application. In this paper, we review the background of compressed sensing development. We introduce the framework of CS and the key technique and illustrate some naïve application on image process.]]>
<![CDATA[Compressed Sensing High-accuracy Detection for Electric Power Interharmonics ]]>
<![CDATA[Tiejun Cao]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v12.i9.pp6494-6501
<![CDATA[Interharmonics frequencies are not integer multiple of the fundamental frequency, and interharmonics amplitudes are far less than fundamental amplitude and harmonics amplitudes, which mean high sensitivity to desynchronization problems, so it’s dificult to estimate interharmonics. In this paper, a new method based on random sparse sampling and compressed sensing (CS) Bregman technique was proposed to estimate the interharmonics. The random sam pling has following advantages; alias-free、sampling frequency need not obey the Nyquist limit、and higher frequency resolution. So the random sampling can measure the signals which their frequencies component are close, and can implement the higher frequencies measurement with lower sampling frequency. However,the rangdom sampling exists the noise in spectrum analysis, so it’s difficult to estimate the low amplitude signals. Compressed sensing can work out this problem by designing observation matrix and with the sparsity reconstruction of the signal in the Fourier domain; in addition, the application of CS can estimate the amplitudes and phases of the signals exactly. The results ofexperiments show that the proposed method can estimate the interharmonics exactly,even if the interharmonics frequencies are close the fundam ental frequency and interharmonics amplitudes are far less than fundamental am plitude；and can measure high order interharmonics with lower sam pling frequency.]]>
<![CDATA[A Controller Design Researh Based on the Cloud Model ]]>
<![CDATA[Feng Jie]]>;
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 3: December 2015 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijeecs.v16.i3.pp531-538
<![CDATA[A novel control structure model is proposed based on cloud model for the first time．The structure model is a nonlinear model in nature, and it can be composed of a group of uncertain reasoning rules easily．NonIinear mapping characteristics of cloud model is analysed in this sudy, and the design method of the intelligent controller is presented based on the structure model, and some simulation examples are showed．]]>
<![CDATA[A High-accuracy Detection Method Research for Electric Power Harmonic ]]>
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 12: December 2014 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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<![CDATA[In this paper, a time-frequency filter is designed，which can detect the frequency, amplitude and phase of any order harmonics and interharmonics in signal by means of time domain convolution．The theory analysis are carried to this method and the calculate formula are concluded, the spectral leakage and the barrier domino offect are shun, the non-integer order wave are eluded, which are engendered in Fourier domain．Experiment simulation results show that time-frequency filtering convolution flunction can be designed and realized neatly and conveniently ; the influences of fundamental frequency fluctuation on harmonic analysis are restrained by using the approach presented in this paper；the relative errors of calculating fundamental frequencies with many order harmonics and interharmonics are no more than 0.00008%, the relative erors of calculating amplitudes are no more than 0.00013%，and those of calculating initial phases are no more than 0.078%． http://dx.doi.org/10.11591/telkomnika.v12i12.6474 ]]>
<![CDATA[Multi-target Direction Measurement on Bistatic MIMO Radar ]]>
<![CDATA[Jingfang Wang]]>
<![CDATA[ Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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<![CDATA[In recent years, multiple-input multiple output (MIMO) radar has been widespread concern in the domestic and foreign researchers. Bistatic radar draws on the great success of MIMO technology in the communications field, and it has many advantages over conventional radar. In this paper, the direction angles estimations of bistatic MIMO radar are researched. To contrast traditional radar DOA estimates, the direction vector of the bistatic MIMO radar is the Knonecker plot of the emission vector and reception vector, that two-dimensional direction angles is estimated. To solve this problem, the principle of bistatic MIMO radar signal model is in-depthly researched.By proposing Capon dimensionality reduction method, the two-dimensional directions of the dual-based MIMO radar are estimated, and computer simulation is to verify the effectiveness of the method. http://dx.doi.org/10.11591/telkomnika.v12i9.4602 ]]>
