To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPT...To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.展开更多
In order to compensate for the deficiency of Sine Pulse Width Modulation（SPWM）, on the base of analyzing the principle of space w tot pulse width modulation and being compared with SPWM, the method of solving workin...In order to compensate for the deficiency of Sine Pulse Width Modulation（SPWM）, on the base of analyzing the principle of space w tot pulse width modulation and being compared with SPWM, the method of solving working time of adjacent vector and the method of generate space voltage vector were introduced. The experiment to the inverter which consists of IGBT proves that SVPWM centrol algorithm can reduce harmonic effectively, it is beneficial to enhancing the utilization rate of voltage source inverter direct current power supply.展开更多
A novel modulation recognition algorithm is proposed by introducing a Chen-Harker-Kanzow-Smale (CHKS) smooth function into the C-support vector machine deformation algorithm. A set of seven characteristic parameters i...A novel modulation recognition algorithm is proposed by introducing a Chen-Harker-Kanzow-Smale (CHKS) smooth function into the C-support vector machine deformation algorithm. A set of seven characteristic parameters is selected from a range of parameters of communication signals including instantaneous amplitude, phase, and frequency. And the Newton-Armijo algorithm is utilized to train the proposed algorithm, namely, smooth CHKS smooth support vector machine (SCHKS-SSVM). Compared with the existing algorithms, the proposed algorithm not only solves the non-differentiable problem of the second order objective function, but also reduces the recognition error. It significantly improves the training speed and also saves a large amount of storage space through large-scale sorting problems. The simulation results show that the recognition rate of the algorithm can batch training. Therefore, the proposed algorithm is suitable for solving the problem of high dimension and its recognition can exceed 95% when the signal-to-noise ratio is no less than 10 dB.展开更多
The aim of modulation classification （MC） is to identify the modulation type of a commtmication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-...The aim of modulation classification （MC） is to identify the modulation type of a commtmication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their recognition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis （PCA） with different transformation inputs, can achieve satisfactory accuracy even at low SNR （as low as 2 dB）. Due to the properties of spectrogram, the statistical pattern recognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.展开更多
With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more serio...With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more seriously.To solve the above problem,three-level neutral point clamped(NPC)inverters have been widely used,but their development is greatly restricted by the defect of neutral point voltage imbalance.In this paper,an improved virtual space vector pulse width modulation(VSVPWM)was proposed.Firstly,the mathematical models of various space vectors were established,and the influence of various space vectors on neutral point voltage was analyzed.The sum of the vector current at the neutral point was zero and the voltage control at the neutral point was completed by.introducing the time offset into different switching times of the redundant small vector.This method was simple in design and avoided the redundant calculation of the traditional VSVPWM method and tedious switch sequence design.This balancing control strategy could greatly reduce the influence of virtual vectors on neutral point voltage and effectively control the low-frequency oscillation of neutral point voltage.The validity of the method was verified by establishing a matlab simulation model.展开更多
Three-level neutral point clamped(NPC)inverters have been widely applied in the high voltage and high power drive fields.The capacitance voltage balancing algorithm is a hot topic that many specialists and scholars ha...Three-level neutral point clamped(NPC)inverters have been widely applied in the high voltage and high power drive fields.The capacitance voltage balancing algorithm is a hot topic that many specialists and scholars have been working on.V arious capacitance voltage balancing strategies have been studied,in which the redundant short vectors are not fully utilized.In order to increase the capacitance voltage control effect of the short vectors,a new algorithm is proposed.展开更多
文摘To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.
文摘In order to compensate for the deficiency of Sine Pulse Width Modulation（SPWM）, on the base of analyzing the principle of space w tot pulse width modulation and being compared with SPWM, the method of solving working time of adjacent vector and the method of generate space voltage vector were introduced. The experiment to the inverter which consists of IGBT proves that SVPWM centrol algorithm can reduce harmonic effectively, it is beneficial to enhancing the utilization rate of voltage source inverter direct current power supply.
基金supported by the National Natural Science Foundation of China(61401196)the Jiangsu Provincial Natural Science Foundation of China(BK20140954)+1 种基金the Science and Technology on Information Transmission and Dissemination in Communication Networks Laboratory(KX152600015/ITD-U15006)the Beijing Shengfeifan Electronic System Technology Development Co.,Ltd(KY10800150036)
文摘A novel modulation recognition algorithm is proposed by introducing a Chen-Harker-Kanzow-Smale (CHKS) smooth function into the C-support vector machine deformation algorithm. A set of seven characteristic parameters is selected from a range of parameters of communication signals including instantaneous amplitude, phase, and frequency. And the Newton-Armijo algorithm is utilized to train the proposed algorithm, namely, smooth CHKS smooth support vector machine (SCHKS-SSVM). Compared with the existing algorithms, the proposed algorithm not only solves the non-differentiable problem of the second order objective function, but also reduces the recognition error. It significantly improves the training speed and also saves a large amount of storage space through large-scale sorting problems. The simulation results show that the recognition rate of the algorithm can batch training. Therefore, the proposed algorithm is suitable for solving the problem of high dimension and its recognition can exceed 95% when the signal-to-noise ratio is no less than 10 dB.
文摘The aim of modulation classification （MC） is to identify the modulation type of a commtmication signal. It plays an important role in many cooperative or noncooperative communication applications. Three spectrogram-based modulation classification methods are proposed. Their recognition scope and performance are investigated or evaluated by theoretical analysis and extensive simulation studies. The method taking moment-like features is robust to frequency offset while the other two, which make use of principal component analysis （PCA） with different transformation inputs, can achieve satisfactory accuracy even at low SNR （as low as 2 dB）. Due to the properties of spectrogram, the statistical pattern recognition techniques, and the image preprocessing steps, all of our methods are insensitive to unknown phase and frequency offsets, timing errors, and the arriving sequence of symbols.
基金Supported by Application Technology Research and Development of Harbin City(2017RAXXJ075)。
文摘With the acceleration of agricultural electrification,a lot of nonlinear and shock loads appear in the rural power grid,and the resulting harmonic and reactive currents pollute the rural power grid more and more seriously.To solve the above problem,three-level neutral point clamped(NPC)inverters have been widely used,but their development is greatly restricted by the defect of neutral point voltage imbalance.In this paper,an improved virtual space vector pulse width modulation(VSVPWM)was proposed.Firstly,the mathematical models of various space vectors were established,and the influence of various space vectors on neutral point voltage was analyzed.The sum of the vector current at the neutral point was zero and the voltage control at the neutral point was completed by.introducing the time offset into different switching times of the redundant small vector.This method was simple in design and avoided the redundant calculation of the traditional VSVPWM method and tedious switch sequence design.This balancing control strategy could greatly reduce the influence of virtual vectors on neutral point voltage and effectively control the low-frequency oscillation of neutral point voltage.The validity of the method was verified by establishing a matlab simulation model.
文摘Three-level neutral point clamped(NPC)inverters have been widely applied in the high voltage and high power drive fields.The capacitance voltage balancing algorithm is a hot topic that many specialists and scholars have been working on.V arious capacitance voltage balancing strategies have been studied,in which the redundant short vectors are not fully utilized.In order to increase the capacitance voltage control effect of the short vectors,a new algorithm is proposed.
