A blind modulation recognition algorithm based on cyclic spectral correlation

Cyclic spectral correlation above the bifrequency plane for the received signal was calculated by the strip spectral correlation algorithm （SSCA）and then was normalized. The result was expressed by matrix. The sum of error-square was computed between corresponding elements for the theoretical sampling matrix of all kinds of modulated signals and calculated matrix. The modulation type was recognized by exploiting the minimum value of the sum of error-square. No extracted characteristic parameter and prior information are needed for identifying the modulation type compared to the conventional methods. In addition, the new method extends the recognition scope and has high recognition probability at low SNR. The simulation results obtained by means of Monter-Carlo method proved the presented algorithm.

WAVELET BASED SPECTRAL CORRELATION METHOD FOR DPSK CHIP RATE ESTIMATION

A wavelet-based spectral correlation algorithm to detect and estimate BPSK signal chip rate is proposed. Simulation results show that the proposed method can correctly estimate the BPSK signal chip rate, which may be corrupted by the quadratic characteristics of the spectral correlation function, in a low SNR environment.

Systematic error suppression scheme of the weak equivalence principle test by dual atom interferometers in space based on spectral correlation

Systematic error suppression and test data processing are very important in improving the accuracy and sensitivity of the atom interferometer(AI)-based weak-equivalence-principle(WEP) test in space. Here we present a spectrum correlation method to investigate the test data of the AI-based WEP test in space by analyzing the characteristics of systematic errors and noises. The power spectrum of the Eotvos coefficient η, systematic errors, and noises in AI-based WEP test in space are analyzed and calculated in detail. By using the method, the WEP violation signal is modulated from direct current(DC) frequency band to alternating current(AC) frequency band. We find that the signal can be effectively extracted and the influence of systematic errors can be greatly suppressed by analyzing the power spectrum of the test data when the spacecraft is in an inertial pointing mode. Furthermore, the relation between the Eotvos coefficient η and the number of measurements is obtained under certain simulated parameters. This method will be useful for both isotopic and nonisotopic AI-based WEP tests in space.

SPECTRAL CORRELATION METHOD IN THE IDENTIFICATION OF FREQUENCY-SELECTIVE FADING RADIO ENVIRONMENT

Many modulated communication signals exhibit a cyclostationarity （or periodic correlation） property. To exploit the underlying periodicity of the modulated signal in the real-time recognition schcme of radio eilvironments, this letter introduces a spectral correlation method to identify the number and the direction of multi-path in the environment of frequency-selective fading channel. By simulation, the graphs of spatial spectra corresponding to a certain cycle frequency is presented to show the accuracy of spectral correlation method in multi-path environment recognition.

Weighted spectral correlation angle target detection method for land‑based hyperspectral imaging

In land-based spectral imaging,the spectra of ground objects are inevitably afected by the imaging conditions(weather conditions,atmospheric conditions,light conditions,zenith and azimuth angle conditions)and spatial distribution of targets,leading to uncertainties featured by“same object diferent spectrum”.That is,the spectrum of a ground object may change within a certain range under diferent imaging conditions.Traditional target detection(TD)methods are mainly based on similarity measurements and do not fully account for the spectral uncertainties.These detection methods are prone to false detections or missed detections.Therefore,reducing the impact of spectral uncertainties on TD is an important research topic in hyperspectral imaging.In this paper,we frst review traditional TD methods and compare their principles and characteristics.It is found that the spectral correlation angle(SCA)method has good adaptability in land-based imaging.The shortcoming of the SCA method that it cannot refect the local spectrum characteristics,is also analyzed.As the efect of spectral uncertainties cannot be completely overcome by the SCA method,a new similarity measurement method,the weighted spectral correlation angle(WSCA)method,is proposed.It can reduce the infuence of spectral uncertainties on TD by increasing the weight of particular bands.Finally,we use two sets of experiments to analyze the efect of the WSCA method on TD.Its performance in overcoming spectral uncertainties caused by variations in imaging conditions or uneven spatial distributions of targets is tested.The results show that the WSCA method can efectively reduce the infuence of spectral uncertainties and obtain a good detection result.

Second-Order Correlation Function for Asymmetric-to-Symmetric Transitions due to Spectrally Indistinguishable Biexciton Cascade Emission

We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exeiton photon is not spectrally distinguishable from the biexciton photon, and either of them can trigger the %tart＇ in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton, the photon statistics will become asymmetric and a cross-bunching lineshape can be obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of g（2）（τ） correlation function measurements.

Analyzing Field-Derived Arboreal Spectral Signatures

Orbital platforms spectral sensitivity can be a major limitation in ascertaining detailed identification and mapping of arboreal ecosystems. Field-derived spectral signatures using a narrow-band sensor, for example, ASD (Analytical Spectral Devices, Boulder, CO, USA) FieldSpec® Pro cover a spectral FR (Full Range) of 350 - 2500 nm exceeding spectral sensitivities of commonly used orbital platforms. The plausibility of deriving a spectral library of trees or forests within a training set is venerable. On the other hand, diagnostic spectral features between tree species or types are inherently difficult to ascertain from orbital platforms. This is so especially when the spectral library is applied to a demarcated region beyond the extents of training set. Basic suborbital limitations in detailed identification of trees and forests are presented in this study. We draw attention to spectral or temporal deficiencies and offer probable solutions depending on preferred or optimal spectral sensitivities. For example, Hyperion with 220 bands (400 - 2500 nm), one of the three primary instruments on the EO-1 spacecraft, has narrow bandwidths and covers the entire range of the spectral profiles collected for North Dakota tree species. With a 30 m spatial resolution, it is still useful in species identification in moderate stands of forest. Hyperion is a tasking satellite with limited passes over North Dakota (≈7% of total area) limiting its use as a platform of choice for statewide forest resource mapping.

Selection of characteristic spectral bands for the analysis by the NIR correlation coefficient method

We analyzed the infrared 0R）-near infrared （NIR） 2D correlation spectra of drugs perturbed by temperature. By identification of functional groups by IR spectrum and by the correlation analysis of IR-NIR spectrum, we identified the characteristic spectral bands that were closely related to the structure of a drug substance of interest. These characteristic spectral bands were relatively less interfered by other ingredients for analysis by the NIR correlation coefficient method. With these characteristic spectral bands, the accuracy of screening illegally added Sildenafil citrate, Tadalafil and Metforrnin hydrochloride in Chinese patent drugs and healthcare products reached about 90%, which met the requirements of rapid screening.

A new multi-model coding algorithm based on MBE and spectral amplitude correlation between successive frames

The researches on spectral amplitude correlation between successive frames based on MBE (Multi-Band Excitation) are presented and a new MBE coding algorithm of muitimodels is proposed. It has been shown that the magnitude spectrum in MBE coding algorithm can be estimated in very high accuracy by using a simple linear predictive model of the spectral amplitude correlation between successive frames. This model employs oniy one gain coefficient and one predictive coefficient. The accuracy of estimated magnitude spectrum in this model is higher than that of the conventional MBE algorithm using the 10-th order LPC (Linear Predictive Coding) Inodel without the spectral amplitude correlation between successlve frames.This model is superior to the conventional MBE coding model in volced speech, but it is iess effective in unvoiced speech, so that the conventional MBE coding algorithm is still used for unvoiced speech. The new multi-model coding algorithm improves the quality of coding speech,and obtains good results

Separating cyclostationary signals from spectrally overlapping interference

This paper studies an algorithm about separating spectrally overlapping signals using the cyclostationary properties of signals.On the basis of direct sequence spread system(DSSS),frequency shift filter is added into the re-ceiver of the communication system.Although the structure of frequency shift filter is more complicated than the time-domain filter,it uses both time correlations and fre-quency spectrum correlations so it can achieve better per-formances on separating the overlapping signals.After the analysis of cyclostationary characteristic and frequency spec-trum correlation,the structure of the frequency shift filter can be gained.Then,a self-adaptive algorithm is utilized for the purpose of achieving optimum multidimensional tap weights of frequency shift components.The simulation results indi-cate that this method can efficiently separate overlapping signals,and its error rate is lower than the time-domain filter or DSSS system by two orders of magnitude on the condition that high-power interference is added into the system.

Establishment of an HPLC method for the analysis of biapenem and its impurities

An HPLC method for routine quality control of biapenem was established.A Dikma Diamonsil C_(18) column(250mm×4.6 mm,5μm) was used with diode array detection and single wavelength detection at 220 nm.The mobile phase was consisted of acetonitrile-0.1%triethylamine water(1:99,v/v).The liner range for biapenem quantification was 0.05-10.0 mg/mL(r^2= 0.999). The LOD and LOQ of impurity were 4.8 ng(S/N = 3) and 18.5 ng(S/N = 10),respectively.Intra-day RSD of main impurity and total impurity were 1.84%and 3.37%(n = 3);inter-day RSD of main impurity and total impurity were 4.84%and 7.58% (n = 9).The test solution was stable when stored at 4℃for 6 h.The impurity peaks of biapenem can be identified by chromatographic spectral correlation analysis using high-performance liquid chromatography-diode array detection data from the quality control method by calculating correlation coefficients without reference standards.Two hydrolysis degradation products with relative retention times(RRTs) of 0.528 and 0.743,two dimers with RRTs of 1.062 and 2.817 were identified in the quality control chromatogram.It provides a new way to identify impurity peaks by the routine HPLC-UV method.

Cyclostationary Modeling of Surface Electromyography Signal During Gait Cycles and Its Application for Cerebral Palsy Diagnosis

Cerebral palsy(CP) is a group of permanent movement disorders that appear in early childhood.The electromyography(EMG) signal analysis and the gait analysis are two most commonly used methods in the clinic. In this paper, a cyclostationary model of the EMG signal is proposed. The model can combine the aforementioned two methods. The EMG signal acquired during the gait cycles is assumed to be cyclostationary due to the physiological characteristics of the EMG signal production. Then, the spectral correlation density is used to analyze the cyclic frequency(corresponding to the gait cycles) and spectral frequency(the frequency of EMG signal) in a waterfall representation of the two kinds of frequencies. The experiments show that the asymptomatic(normal) subjects and symptomatic subjects(with CP) can be distinguished from the spectral correlation density in a range of cyclic frequencies.

Establishment of an HPLC method for the analysis of biapenem and its impurities

An HPLC method for routine quality control of biapenem was established. A Dikma Diamonsil Cls column （250 mm× 4.6 mm, 5 μm） was used with diode array detection and single wavelength detection at 220 mm. The mobile phase was consisted of acetonitrile-0 1% triethylamine water （1：99, v/v）. The liner range for biapenem quantification was 0.05-10.0 mg/mL （r2- 0.999）. The LOD and LOQ of impurity were 4.8 ng （S/N 3） and 18.5 ng （S/N = 10）, respectively. Intra-day RSD of main impurity and total impurity were 1.84% and 3.37% （n = 3）; inter-day RSD of main impurity and total impurity were 4.84% and 7.58% （n = 9）. The test solution was stable when stored at 4 ℃ for 6 h. The impurity peaks of biapenem can be identified by chromatographic spectral correlation analysis using high-performance liquid chromatography~tiode array detection data from the quality control method by calculating correlation coefficients without reference standards. Two hydrolysis degradation products with relative retention times （RRTs） of 0.528 and 0.743, two dimers with RRTs of 1.062 and 2.817 were identified in the quality control chromatogram. It provides a new way to identify impurity peaks by the routine HPLC-UV method.

Causality Analysis of Futures Sugar Prices in Zhengzhou Based on Graphical Models for Multivariate Time Series

This paper presents a method of constructing a mixed graph which can be used to analyze the causality for multivariate time series.We construct a partial correlation graph at first which is an undirected graph.For every undirected edge in the partial correlation graph,the measures of linear feedback between two time series can help us decide its direction,then we obtain the mixed graph.Using this method,we construct a mixed graph for futures sugar prices in Zhengzhou（ZF）,spot sugar prices in Zhengzhou（ZS） and futures sugar prices in New York（NF）.The result shows that there is a bi-directional causality between ZF and ZS,an unidirectional causality from NF to ZF,but no causality between NF and ZS.