Any OFDM-based wireless communication receiver relies on channel estimation. Across a wireless multipath fading channel, there is a growing need for high-data-rate communication, which typically demands previous chann...
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Due to the good adaptability of wavelet theory in signalprocessing, its current application fields are very extensive. This paper first summarizes the application fields of current wavelet theory and analyzes the cha...
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Due to the good adaptability of wavelet theory in signalprocessing, its current application fields are very extensive. This paper first summarizes the application fields of current wavelet theory and analyzes the characteristics of wavelet analysis theory. Then, several methods for fault diagnosis of traditional inverter circuits are listed. The limitations of their fault diagnosis in new multi-level inverter circuits are analyzed. The wavelet analysis is applied to the fault diagnosis of multi-level inverter circuits. After analyzing the fault mode of the multi-level inverter circuit, the wavelet packet is used to extract the fault features, and then the support vector machine theory is combined to diagnose the fault. Finally, the method described in this paper is verified by Simulink simulation software, and the accuracy of the method is more than 90%. The method is feasible and effective.
Differential capacitance detection, a common high resolution proof mass displacement detection scheme, is adopted in the gyroscope to measure the rotor deflection angle by installing an electrode with four poles under...
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The demand increasing for the high fidelity portable devices has laid emphasis on the development of low power and high performance systems. Binary addition is the most basic operation found in arithmetic components. ...
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Transfer learning aims to transfer knowledge from the labelled source domain data to build a good classifier for the target domain data which has few labels or none. Existing feature-based transfer learning methods se...
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Transfer learning aims to transfer knowledge from the labelled source domain data to build a good classifier for the target domain data which has few labels or none. Existing feature-based transfer learning methods seek to transform the data to a new feature space under which the distribution discrepancy is reduced. However, data in different classes may not be easy to be separated in the new feature representation. Therefore, a modified transfer learning algorithm with Joint Distribution Adaptation(JDA) and Maximum Margin Criterion(MMC) is put forward in this paper, which we call MMC-JDA for short. MMC-JDA is aimed at minimizing the distribution discrepancy between two domains and maximizing the separability of each class at the same time. Comparative experiments on 16 cross-domain public image datasets show that MMC-JDA is effective and performs better than several common transfer learning methods.
Frequency diverse array(FDA) which employs a small frequency increment between adjacent elements can provide a range-angle-dependent beampattern with new application potentials. In this paper, the proposed coherent pu...
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Frequency diverse array(FDA) which employs a small frequency increment between adjacent elements can provide a range-angle-dependent beampattern with new application potentials. In this paper, the proposed coherent pulsed-LFM FDA scheme enables full spatial coverage with a single transmit waveform, wherein the transmit beamforming can be performed at the receiver with flexible signalprocessing means. In the coherent pulsedLFM FDA radar configuration, the range sidelobe level(SLL) can be reduced significantly. Analyses of the multi-dimensional ambiguity function in terms of the low sidelobe characteristics, spatial coverage capability, and resolution properties in range, angle and Doppler domains are given by ambiguity function profiles. Comparisons with conventional phased array and MIMO(Multiple-Input Multiple-Output) radar are presented in the simulation. Results demonstrate the superiority of the proposed approach in angular coverage and sidelobe level with simplicity in engineering.
Digital signal processor (DSP) is widely used in wireless communications to compute fast Fourier transform (FFT) or its inverse (IFFT). This paper presents the butterfly unit (BU) suitable for DSP to compute FFT/IFFT....
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ISBN:
(纸本)9789811317477;9789811317460
Digital signal processor (DSP) is widely used in wireless communications to compute fast Fourier transform (FFT) or its inverse (IFFT). This paper presents the butterfly unit (BU) suitable for DSP to compute FFT/IFFT. The dynamic range of input sequence is increased by representing them using 16-bit floating format. The BU performs trivial addition as well as complex multiplication in a single cycle. The proposed BU is free from multiple processing elements. This BU also eliminates the rounding of twiddle coefficients occurred in fixed-point data representation and reduces the error.
In the 5 generation mobile communication(5G) system, it is required to provide three different types of services, including enhanced Mobile Broadband(eMBB), massive machine-type communication(mMTC), and ultra-re...
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In the 5 generation mobile communication(5G) system, it is required to provide three different types of services, including enhanced Mobile Broadband(eMBB), massive machine-type communication(mMTC), and ultra-reliable and low-latency communication(URLLC).To meet all those demand in 5G, the waveform is crucial. Although the CP-OFDM waveform has been wildly used in 4G, it is hardly to satisfy the requirements of 5G.A lot of candidate waveforms are discussed for 5G system, including UFMC, FBMC, F-OFDM etc. In this paper, the UFMC waveform is discussed, the different filters and different frequency width of the subband in UFMC system are studied and appropriate parameters for the system are recommended.
In the view of the target dense region, the feartures of different target39;s time difference are not obvious, which leads to the problem of JTIDS multi-user sorting useless based on time difference. A nonlinear tra...
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In the view of the target dense region, the feartures of different target's time difference are not obvious, which leads to the problem of JTIDS multi-user sorting useless based on time difference. A nonlinear transformation sorting algorithm of high-order cumulant based on doppler frequency shift is proposed: First of all,make the nonlinear transformation based on the second order cumulant,the sixth order cumulant, the normalized skewness and the normalized kurtosis for single station signals respectively, achiece a sharp rise occurs in the degree of the frequency shift;Then,build the eigenvector according to the transformation;Finally,use spectral clustering algorithm to cluster the datasets. Simulation experiments were carried out,based on four targets which could not be sorted by the time difference. The result showed that compared with the traditional method,the success rate of our method was significantly improved, and the effectiveness of the algorithm was verified.
Aiming at the problem that square integral bispectrum cannot accurately represent communication transmitter individuals with the same type under small sample, a communication transmitter individual deep square integra...
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Aiming at the problem that square integral bispectrum cannot accurately represent communication transmitter individuals with the same type under small sample, a communication transmitter individual deep square integral bispectra feature extraction method based on stacked autoencoder network is proposed. The square integral bispectrum(SIB) features of real communication transmitters signals were extracted firstly from the instantaneous frequency. Then the deep SIB features were represented through the layer-wise semi-supervised learning by a stacked autoencoder network. Experiments on real FM communication transmitter signals showed that the identification accuracy is around 80% and the results of multiple experimental variables setting indicated the robustness of the algorithm proposed.
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