EM-based detection scheme for differential unitary space-time modulation

The performance loss of an approximately 3 dB signal-to-noise ratio is always paid with conventional differential detection compared to the related coherent detection. A new detection scheme consisting of two steps is proposed for the differential unitary space-time modulation （DUSTM） system. In the first step, the data sequence is estimated by conventional unitary space-time demodulation （DUSTD） and differentially encoded again to produce an initial estimate of the transmitted symbol stream. In the second step, the initial estimate of the symbol stream is utilized to initialize an expectation maximization （EM）-based iterative detector. In each iteration, the most recent detected symbol stream is employed to estimate the channel, which is then used to implement coherent sequence detection to refine the symbol stream. Simulation results show that the proposed detection scheme performs much better than the conventional DUSTD after several iterations.

Multiple symbol differential detection based on sphere decoding for unitary space-time modulation

Recently, a multiple symbol differential （MSD） sphere decoding （SD） algorithm for unitary spacetime modulation over quasi-static channel has been proved to achieve the performance of maximumlikelihood （ML） detection with relatively low complexity. However, an error floor occurs if the algorithm is applied over rapid-fading channels. Based on the assumption of continuous fading, a multiple symbol differential automatic sphere decoding （MSDASD） algorithm is developed by incorporating a recursive form of an ML metric into automatic SD （ASD） algorithm. Furthermore, two algorithms, termed as MSD approximate ASD （MSDAASD） and MSD pruning ASD （MSDPASD）, are proposed to reduce computational complexity and the number of comparisons, respectively. Compared with the existing typical algorithms, i.e., multiple symbol differential feedback detection （MS-DFD） and noncoherent sequence detection （NSD）, the performance of the proposed algorithms is much superior to that of MS-DFD and a little inferior to that of NSD, while the complexity is lower than that of MS-DFD in most cases and significantly lower than that of NSD.

Joint-state differential detection algorithm and its application in UWB wireless communication systems

In this paper, a novel concept of the joint state of input and output of encoder is proposed. Based on it, a recursive algorithm that implements the multi-symbol differential detection in criterion of maximum likelihood is proposed. Simulation results show that its performance can approach to the theoretical boundary of multi-symbol differential detection without increasing the complexity per symbol, and it is effective in practical systems. It is also an optimal algorithm to solve the problems of estimating the state sequence of finite-state Markov process observed in memoryless noise.

Development of Multi-PCR for Differentiation of Vaccine Strain and Field Isolate of Porcine Pseudorabies Virus

Three pairs of primer were designed for amplification of porcine pseudorabies virus （PRV） gB, gE, and TK gene by multiplex PCR （multi-PCR） in order to differentiate vaccine strains from field isolates. Three specific bands were obtained respectively at the expected size, 427 bp （gB gene）, 298 bp （gEgene）, and 208 bp （TKgene）, Then four different gene-deleted vaccines of PRV were detected by multi-PCR. One ex- pected specific band was observed in one of samples, while two bands in the others. As shown by the detection results, the multi-PCR has high sensitivity and specificity and should be applied in pathogen diagnosis and epidemiological investigation in the future.

Application of transmit diversity for improved robust watermarking

Many common multimedia signal processing, including cropping, filtering, and perceptual coding, make watermark signal fading-like modification. A scheme that applies transmit diversity technique to improve robustness of digital watermarking is presented. First, the scheme decomposes the original image using wavelet pyramid algorithm and chooses the middle-frequency band for transmission channel that the watermark will be embedded into. Then the watermark is pseudo-randomly permuted. The scheme makes use of space-time coding and differential detection technique to embed and extract watermark. The extracting process has access to neither the original image nor channel state information. Experimental results demonstrate that the scheme improves the performance of robust watermarking.

Design of a Weak Signal Detecting Circuit in the Infrared Spectrum Absorbed Type Gas Sensor

In the infrared spectrum absorbed type gas concentration sensor,voltage signal obtained from the two-channel thermopile infrared detector TPS2534 is very weak.In order to solve this problem,the authors have established the structure of the sensor and designed weak signal detecting circuit of the sensor based on infrared spectrum absorption principle,differential de-noising principle and weak signal detecting principle.The authors have made experiments using CH4 gas.The results show that the circuit can remove noise effectively and detect weak electrical signal obtained from the detector.

BER ANALYSIS OF A GMSK SYSTEM USING DECISION FEEDBACK

There are considerable literatures on the Bit Error Rate(BER)evaluation of DifferentialDetection of Gaussian Minimum Shift Keying(DDGMSK)system using Decision Feedback(DF),butmost of them give the performance based on the Monte Carlo Error Counting(MCEC)technique.Fromthe probability distribution of the phase angle between two vectors perturbed by Gaussian noises,theformulae of BER are derived for the performance analysis of DDGMSK system with DF in this letter.Considering the m-bit dock-tailed sequence,the new formulae of Gaussian Minimum Shift Keying(GMSK)modulated phase and the Time-Varying Signal to Noise Ratio(TVSNR)of the demodulatedsignal are presented,and it is proved that the relationship between the TVSNR of the demodulatedsignal and the size of eye opening is not inevitable.Simulation results show that the theoretical in-vestigation gives analogous results with the MCEC technique.The formulae presented are useful for theperformance analysis of systems using GMSK as modulating and demodulating method,for instance,the analysis of synchronous performance of frequency-hopping communication system.

Effect of Water Vapor Absorption on Measurements of Atmospheric Nitrate Radical by LP-DOAS

During the measurement of atmospheric nitrate radical by long-path differential optical absorption spectroscopy, water vapor strong absorption could affect the measurement of nitrate radical and detection limits of system. Under the tropospheric condition, the optical density of water vapor absorption is non-linearly dependent on column density. An effective method was developed to eliminate the effect of water vapor absorption. Reference spectra of water vapor based on the daytime atmospheric absorption spectra, when fitted together with change of cross section with water vapor column densities, gave a more accurate fitting of water vapor absorptions, thus its effect on the measurements of nitrate radical could be restricted to a minimum and detection limits of system reached 3.6 ppt. The modified method was applied during an intensive field campaign in the Pearl River Delta, China. The NO3 concentration in polluted air masses varied from 3.6 ppt to 82.5 ppt with an average level of 23.6±1.8 ppt.

The progress on the estimation of DNA methylation level and the detection of abnormal methylation

Background:DNA methylation is a key heritable epigenetic modification that plays a crucial role in transcriptional regulation and therefore a broad range of biological processes.The complex patterns of DNA methylation highlight the significance of the profiling the DNA methylation landscape.Results:In this review,the main high-throughput detection technologies are summarized,and then the three trends of computational estimation of DNA methylation levels were analyzed,especially the expanding of the methylation data with lower coverage.Furthermore,the detection methods of differential methylation patterns for sequencing and array data were presented.Conclusions:More and more research indicated the great importance of DNA methylation changes across different diseases,such as cancers.Although a lot of enormous progress has been made in understanding the role of DNA methylation,only few methylated genes or functional elements serve as clinically relevant cancer biomarkers.The bottleneck in DNA methylation advances has shifted from data generation to data analysis.Therefore,it is meaningful to develop machine learning models for computational estimation of methylation profiling and identify the potential biomarkers.

Comparison of diagnostic value of TIRADS,BSRTC,BRAF^(V600E) mutation detection and their combined use in differentiating thyroid nodules

Objective To compare the diagnostic efficiency of the thyroid imaging reporting and data system(TIRADS),the Bethesda system for reporting thyroid cytopathology(BSRTC)and BRAFV600Edetection,and their combined use in the differentiation between benign and malignant thyroid nodules.Methods One hundred

A Fault-tolerance Estimating Method for Ionosphere Corrections in Satellite Navigation System

Aiming to the reliable estimates of the ionosphere differential corrections for the satellite navigation system in the presence of the ionosphere anomaly, a fault-tolerance estimating method, which is based on the distributed Kalman filtering, is proposed. The method utilizes the parallel sub-filters for estimating the ionosphere differential corrections. Meanwhile, an infinite norm （IN） method is proposed for the detection of the ionosphere irregularity in the filter processing. Once the anomaly is detected, the sub-filter contaminated by the anomaly measurements will be excluded to ensure the reliability of the estimates. The simulation is conducted to validate the method and the results indicate that the anomaly can be found timely due to the novel fault detection method based on the infinite norm. Because of the parallel sub-filter architecture, the measurements are classified by the spatial distribution so that the ionosphere anomaly can be positioned and excluded more easily. Thus, the method can provide the robust and accurate ionosphere differential corrections.