Modeling Distortion Signals of Power Grid Based on Wiener-G Functionals

The uniform mathematical model of distortion signals in power grid has been setup with the theory of Wiener-G Functional. Firstly,the Matlab simulation models were established. Secondly,the Wiener kernel of power load was found based on the Gaussian white noise as input. And then the uniform mathematical model of the power grid signal was established according to the homogeneous of the same order of Wiener functional series. Finally,taking three typical distortion sources which are semiconductor rectifier,electric locomotive and electric arc furnace in power grid as examples,we have validated the model through the Matlab simulation and analyzed the simulation errors. The results show that the uniform mathematical model of distortion signals in power grid can approximation the actual model by growing the items of the series under the condition of the enough storage space and computing speed.

PSO-DBNet for Peak-to-Average Power Ratio Reduction Using Deep Belief Network

Data transmission through a wireless network has faced various signal problems in the past decades.The orthogonal frequency division multiplexing(OFDM)technique is widely accepted in multiple data transfer patterns at various frequency bands.A recent wireless communication network uses OFDM in longterm evolution(LTE)and 5G,among others.The main problem faced by 5G wireless OFDM is distortion of transmission signals in the network.This transmission loss is called peak-to-average power ratio(PAPR).This wireless signal distortion can be reduced using various techniques.This study uses machine learning-based algorithm to solve the problem of PAPR in 5G wireless communication.Partial transmit sequence(PTS)helps in the fast transfer of data in wireless LTE.PTS is merged with deep belief neural network(DBNet)for the efficient processing of signals in wireless 5G networks.Result indicates that the proposed system outperforms other existing techniques.Therefore,PAPR reduction in OFDM by DBNet is optimized with the help of an evolutionary algorithm called particle swarm optimization.Hence,the specified design supports in improving the proposed PAPR reduction architecture.

Robust digital receiver for EPC sensor network

A robust digital receiver based on a matched filter （MF） is proposed for the radio frequency identification （RFID） reader system to enhance the reliability of signal processing in the electronic product code （EPC） sensor network （ESN）. The performance of the proposed receiver is investigated by examining the anti-collision algorithm in the EPC global Class1 Generation2 protocol. The validity and usefulness are demonstrated by both computer simulations and experiments. Based on the verification results, comparing with the conventional zero crossing detector （ZCD） based receiver, the proposed receiver is very robust against strong amplitude distortions and considerable frequency deviations happening on the backscattered signal from a passive tag.

A Simple Superresolution Approach of Multipath Delay Profiles Measured by PN Correlation Method

Time resolution of multipath delay profiles measured by using autocorrelation of pseudonoise (PN) code sequence is generally limited by the chip rate of the PN code sequence. In this paper, we propose a simple method to improve the time resolution of delay profiles measured by the PN correlation method. Effectiveness of this method is demonstrated by indoor wireless propagation experiments.

Dispersion-Induced Waveform Distortion Detection in 42.7 Gbps CS-RZ Signals by Optical Time Domain Level Monitoring

We propose a technique for chromatic dispersion monitoring based on optical time domain level monitoring. Experimental and simulation results show that the technique is effective for the monitoring of dispersion in 42.7-Gbps CS-RZ signals for dynamic dispersion compensation.

Numerical simulations of the impact of wavefront phase distortions of pump on the beam quality of OPA

A numerical model of optical parametric amplification （OPA） is introduced to investigate the impact of wavefront phase distortion of pump on the beam quality of signal. Numerical results show that the unidentical walk-off directions of the pump and the idler waves are the main factors leading to the transfer of wavefront phase distortions of the pump to the signal, and by reducing the angle between the two directions, the beam quality factor （M2） can be greatly decreased and hence the good beam quality of the signal can be maintained.

Adaptive interference hyperspectral image compression with spectrum distortion control

As one of the next generation imaging spectrometers, interferential spectrometer has been paid much attention. With traditional spectrum compression methods, the hyperspectral images generated by interferential spectrometer can only be protected with better visual quality in spatial domain, but its optical applications in Fourier domain are often ignored. So the relation between the distortion in Fourier domain and the compression in spatial domain is analyzed in this letter. Based on this analysis, a novel coding scheme is proposed, which can compress data in spatial domain while reducing the distortion in Fourier domain. The bitstream of set partitioning in hierarchical trees （SPIHT） is truncated by adaptively lifting the rate-distortion slopes of zerotrees according to the priorities of optical path difference （OPD） based on rate-distortion optimization theory. Experimental results show that the proposed scheme can achieve better performance in Fourier domain while maintaining the image quality in spatial domain.

An improved partial SPIHT with classified weighted rate-distortion optimization for interferential multispectral image compression

Based on the property analysis of interferential multispectral images, a novel compression algorithm of partial set partitioning in hierarchical trees （SPIHT） with classified weighted rate-distortion optimization is presented. After wavelet decomposition, partial SPIHT is applied to each zero tree independently by adaptively selecting one of three coding modes according to the probability of the significant coefficients in each bitplane. Meanwhile the interferential multispectral image is partitioned into two kinds of regions in terms of luminous intensity, and the rate-distortion slopes of zero trees are then lifted with classified weights according to their distortion contribution to the constructed spectrum. Finally a global rate- distortion optimization truncation is performed. Compared with the conventional methods, the proposed algorithm not only improves the performance in spatial domain but also reduces the distortion in spectral domain.

High performance 14-bit pipelined redundant signed digit ADC

A novel architecture of a pipelined redundant-signed-digit analog to digital converter（RSD-ADC） is presented featuring a high signal to noise ratio（SNR）, spurious free dynamic range（SFDR） and signal to noise plus distortion（SNDR） with efficient background correction logic. The proposed ADC architecture shows high accuracy with a high speed circuit and efficient utilization of the hardware. This paper demonstrates the functionality of the digital correction logic of 14-bit pipelined ADC at each 1.5 bit/stage. This prototype of ADC architecture accounts for capacitor mismatch, comparator offset and finite Op-Amp gain error in the MDAC（residue amplification circuit）stages. With the proposed architecture of ADC, SNDR obtained is 85.89 d B, SNR is 85.9 d B and SFDR obtained is 102.8 d B at the sample rate of 100 MHz. This novel architecture of digital correction logic is transparent to the overall system, which is demonstrated by using 14-bit pipelined ADC. After a latency of 14 clocks, digital output will be available at every clock pulse. To describe the circuit behavior of the ADC, VHDL and MATLAB programs are used. The proposed architecture is also capable of reducing the digital hardware. Silicon area is also the complexity of the design.