Digital discrimination of neutrons and γ rays with organic scintillation detectors in an 8-bit sampling system using frequency gradient analysis

The feasibility of using frequency gradient analysis (FGA), a digital method based on Fourier transform, to discriminate neutrons and γ rays in the environment of an 8-bit sampling system has been investigated. The performances of most pulse shape discrimination methods in a scintillation detection system using the time-domain features of the photomultiplier tube anode signal will be lower or non-effective in this low resolution sampling system. However, the FGA method using the frequency-domain features of the anode signal exhibits a strong insensitivity to noise and can be used to discriminate neutrons and γ rays in the above sampling system. A detailed study of the quality of the FGA method in BC501A liquid scintillators is presented using a 5 G samples/s 8-bit oscilloscope and a 14.1 MeV neutron generator. A comparison of the discrimination results of the time-of-flight and conventional charge comparison (CC) methods proves the applicability of this technique. Moreover, FGA has the potential to be implemented in current embedded electronics systems to provide real-time discrimination in standalone instruments.     

Toward a fractal spectrum approach for neutron and gamma pulse shape discrimination

Accurately selecting neutron signals and discriminating 7 signals from a mixed radiation field is a key research issue in neutron detection.This paper proposes a fractal spectrum discrimination approach by means of different spectral characteristics of neutrons and 7 rays.Figure of merit and average discriminant error ratio are used together to evaluate the discrimination effccts.Different neutron and γ signals with various noise and pulse pile-up are simulated according to real data in the literature.The proposed approach is compared with the digital charge integration and pulse gradient methods.It is found that the fractal approach exhibits the best discrimination performance,followed by the digital charge integration method and the pulse gradient method,respectively.The fractal spectrum approach is not sensitive to high frequency noise;and pulse pile-up.This means that the proposed approach has superior performance for effective and efficient anti-noise and high discrimination in neutron detection.     

Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

We report the results of using the fast independent component analysis （FastICA） algorithm to realize Mind extraction of chaotic signals. Two cases are taken into consideration： namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail It is also shown that regarding a noise as an independent source is not always correct.     

Trapezoidal pulse shaping for pile-up pulse identification in X-ray spectrometry

Energy resolution is affected by the intrinsic energy resolution of the detector, ballistic deficit, pile-up pulses and noise. Pile-up pulses become the dominant factor that degrades energy resolution after the system is established, so pile-up rejection is often applied to obtain good energy resolution by discarding pulses that are expected to be contaminated by pile-up. However, pile-up rejection can reduce count rates and thus lower the measurement precision. In order to improve count rates and maintain energy resolution, a new method of pile-up pulse identification based on trapezoidal pulse shaping is presented. Combined with pulse width discrimination, this method is implemented by recording pulses that are not seriously piled up. Some experimental tests with a Cu-Pb alloy sample are carried out to verify the performance of this method in X-ray spectrometry. The results show that the method can significantly improve count rates without degrading energy resolution.     

Denoising lidar signal by combining wavelet improved threshold with wavelet domain spatial filtering

Lidar is an effective tool for remotely monitoring target or object, but the lidar signal is often affected by various noises or interferences. Therefore, detecting the weak signals buried in noises is a fundamental and important problem in the lidar systems. In this paper, an effective noise reduction method combining wavelet improved threshold with wavelet domain spatial filtration is presented to denoise pulse lidar signal and is investigated by detecting the simulating pulse lidar signals in noise. The simulation results show that this method can effectively identify the edge of signal and detect the weak lidar signal buried in noises.     

M-ary information processing via an optimal nonlinear detector

This paper presents a novel approach of M-ary baseband pulse amplitude modulated signal processing via a parameter-optimized nonlinear dynamic system.This nonlinear system usually shows the phenomenon of stochastic resonance by adding noise.To thoroughly discuss the signal processing performance of the nonlinear system,we tune the system parameters to obtain a nonlinear detector with optimal performance.For characterizing the output of the nonlinear system,the derivation of the probability of detection error is given by the system response speed and the probability density function of the nonlinear system output.By varying the noise intensity with fixed system parameters,the phenomenon of stochastic resonance is shown and by tuning the system parameters with fixed noise,the probability of detection error is minimized and the nonlinear system is optimized.The detection performance of the two cases is compared with the theoretical probability of detection error,which is validated by numerical simulation.     

The application of distributed Raman amplification in an all optical network

The effect of distributed Raman amplification (DRA) on the optical signal to noise ratio (OSNR) of an all optical network (AON) is examined by analyzing two types of node isolated principal (NIP). Based on the parameters used in calculation, it is found that in the first case of NIP, the OSNR of a signal passing through such AON can be improved by about 8 dB compared with no DRA. Whereas in the second case of NIP, the OSNR of the signal can be reduced by 11 dB. This kind of phenomena is analyzed and attributed to the dependence of noise figure of amplification system on the way of the active amplification utilization.     

Theory of noise in a kilo-Hz cascaded high-energy Yb-doped nanosecond pulsed fiber amplifier

A theoretical analysis of noise in a high-power cascaded fiber amplifier is presented. Unlike the noise theory in low power communication, the noise of a high power system is redefined as the leaked output energy between pulses with coherent beat noise uncounted. This definition is more appropriate for high power usage in which the pulse energy receives more attention than the pulse shape integrity. Then the low power pre-amplifying stages are considered as linear amplification and analyzed by linear theory. In the high-power amplification stages, the inversion is assumed to recover linearly in the time interval between pulses. The time shape of the output pulse is different from that of the input signal because of different gains at the front and back ends of the pulse. Then, a criterion is provided to distinguish the nonlinear and linear amplifications based on the signal-to-noise ratio （SNR） analysis. Then, an experiment that shows that the output SNR actually drops off in nonlinear amplification is performed. The change in the noise factor can be well evaluated by pulse shape distortion.     

Digital discrimination of neutron and γ ray using an organic scintillation detector based on wavelet transform modulus maximum

A novel algorithm for the discrimination of neutron and γ -ray events with wavelet transform modulus maximum (WTMM) in an organic scintillation has been investigated. Voltage pulses arising from a BC501A organic liquid scintillation detector in a mixed radiation field have been recorded with a fast digital sampling oscilloscope. The WTMM method using frequency-domain features exhibits a strong insensitivity to noise and can be used to discriminate neutron and γ -ray events based on their different asymptotic decay trend between the positive modulus maximum curve and the negative modulus maximum curve in the scale-space plane. This technique has been verified by the corresponding mixed-field data assessed by the time-of-flight (TOF) method and the charge comparison (CC) method. It is shown that the characterization of neutron and γ ray achieved by the discrimination method based on WTMM is consistent with that afforded by the TOF method and better than the CC method. Moreover, the WTMM method itself has presented its ability to eliminate the noise without any pretreatment to the pulses.     

Study of n-γ discrimination for 0.4-1 MeV neutrons using the zero-crossing method with a BC501A liquid scintillation detector

An experimental system aimed at n-γ discrimination using the zero-crossing method with a φ3’’×2’’ BC501A liquid scintillation detector was established and tested with an Am-Be neutron source. Two-dimensional plots of energy versus zero-crossing time were obtained. The quality of n-γ discrimination was checked by the figure-of-merit (FOM), the neutron peak-to-valley ratio, and the proportion of leaked neutrons over all neutron events. The performance of n-γ discrimination in terms of FOM was compared with previous work done by other groups. The n-γ discrimination in four different energy regions with an interval of 0.1 MeV between 0.3 MeV and 0.7 MeV was studied, and the results indicate that the n-γ discrimination threshold can go down to 0.4 MeV.     

Comparison of simultaneous signals obtained from a dual-field-of-view lidar and its application to noise reduction based on empirical mode decomposition

Although the empirical mode decomposition (EMD) method is an effective tool for noise reduction in lidar signals, evaluating the effectiveness of the denoising method is difficult. A dual-field-of-view lidar for observing atmospheric aerosols is described. The backscattering signals obtained from two channels have different signal-to-noise ratios (SNRs). The performance of noise reduction can be investigated by comparing the high SNR signal and the denoised low SNR signal without a simulation experiment. With this approach, the signal and noise are extracted to one intrinsic mode function (IMF) by the EMD- based denoising; thus, the threshold method is applied to the IMFs. Experimental results show that the improved threshold method can effectively perform noise reduction while preserving useful sudden-change information.     

Measurement of X-ray photon energy and arrival time using a silicon drift detector

Detecting the X-ray emission of pulsars and obtaining the photons' time of arrival are the foundational steps in autonomous navigation via X-ray pulsar measurement. The precision of a pulse's time of arrival is mainly determined by the precision of photon arrival time measurement. In this work, a silicon drift detector is used to measure photon energy and arrival time. The measurement system consists of a signal detector, a processing unit, a signal acquisition unit and a data receiving unit. This system acquires the energy resolution and arrival time information of photons. In particular, background noise with different energies disturbs pulse profile forming, the system can also achieve a high signal-to-noise ratio profile. Ground test results show that this system can be applied in autonomous navigation based on X-ray pulsar measurement.     

Range estimation by Doppler of multi-linein radiated noise spectrum

A method by applying Doppler frequency shift of multi-line in radiated noise spectrum to estimate the vertical range from a receiver to a moving vessel, which is supposed to move along a straight line at a constant velocity, is developed. This method is based on passive ranging by a single sensor and the depth of the sea and other environment parameters are not necessarily known. First the Wigner-Ville distribution is used as the instantaneous frequency estimator to find out the instantaneous frequencies of the muti-lines as a signal. Then define Doppler frequency shift basis functions, based on an algorithm called matching pursuit, by a searching strategy of variable span, and explore the minimum spatial distance between the signal and the Doppler frequency shift basis functions in a five-dimension space. The basis function of the obtained minimum spatial distance corresponds to the estimation of range and speed of the moving vessel. Computer simulations yield statistics errors in the range and speed estimates with differing intensities of noise. If the white noise deviation is less than 10% of the maximum Doppler frequency shift and time-window width is 1.47 times of reference-duration, relative error of range estimate is less than 5.4% and relative error of speed estimate is less than 1.4%. This estimation method has been tested and the result conforms to data collected during an experiment on the sea, the estimated speed is 52 knots and the estimated range is 42 m. The single point passive ranging method can be used for ranging purposes in sonar-buoys, mines, movement analysis of an underwater object in underwater acoustics experiment, and sound source level measurements.     

Experimental research on sound pulse propagation and channel match in shallow water

Theoretical and experimental research of low frequency pulse compression and channel match in shallow water sound channel were carried out based on 2000-Winter Yellow Sea experiment. Using pulse compression method, signals with high signal to noise ratio (SNR) were received over range of 110 kilometers in the experiment. The SNR gain in the process is consistent with the theoretical prediction. The experimental measurement indicated that the channel is highly coherent over a length of 500 s. Channel match method was used to compensate the degradation of pulse compression SNR caused by the multi-path propagation. And the SNR gain in the channel match process can be theoretically predicted. Experimental results show that low frequency pulse compression and channel match method can be used in shallow water sound channel to improve the SNR.     

Faithful quantum entanglement sharing based on linear optics with additional qubits

This paper presents a scheme for faithfully distributing a pure entanglement between two parties over an arbitrary collective-noise channel with linear optics. The transmission is assisted by an additional qubit against collective noise. The receiver can take advantage of the time discrimination and the measurement results of the assistant qubit to reconstruct a pure entanglement with the sender. Although the scheme succeeds probabilistically, the resource used to get a pure entanglement state is finite, and so is easier to establish entanglement in practice than quantum entanglement purification.     

Effect of Time Delay on Binary Signal Detection via a Bistable System

The effect of time delay on binary signal detection via a bistable system in the presence of white or colored Gaussian noise is investigated. By defining the bit error rate based on the solution of the approximated Fokker- Planck equation, the detector performance is investigated theoretically and is verified by Monte Carlo simulation. It is shown that, when the system parameter or noise intensity is optimally chosen, the increasing time delay generally improves the system performance. It is also shown that it is more difficult to accurately predict the system performance with a larger time delay and correlation time. This may inspire more thorough investigations in cooperative effects of a nonlinear system and time delay on signal processing.     

A nonequilibrium phase transition in immune response

The dynamics of immune response correlated to signal transduction in immune thymic cells (T cells) is studied. In particular, the problem of the phosphorylation of the immune-receptor tyrosine-based activation motifs (ITAM) is explored. A nonlinear model is established on the basis of experimental observations. The behaviours of the model can be well analysed using the concepts of nonequilibrium phase transitions. In addition, the Riemann－Hugoniot cusp catastrophe is demonstrated by the model. Due to the application of the theory of nonequilibrium phase transitions, the biological phenomena can be clarified more precisely. The results can also be used to further explain the signal transduction and signal discrimination of an important type of immune T cell.     

Bulk and surface damages in complementary bipolar junction transistors produced by high dose irradiation

Two complementary types NPN and PNP of bipolar junction transistors(BJTs) were exposed to high dose of neutrons and gamma rays. The change in the base and collector currents, minority carriers lifetime, and current gain factor β with respect to the dose were analyzed. The contributions of the base current according to the defect types were also reported.It was declared that the radiation effect of neutrons was almost similar between the two transistor types, this effect at high dose may decrease the value of β to less than one. The Messenger-Spratt equation was used to describe the experimental results in this case. However, the experimental data demonstrated that the effect of gamma rays was generally higher on NPN than PNP transistors. This is mainly attributed to the difference in the behavior of the trapped positive charges in the SiO_2 layers. Meanwhile, this difference tends to be small for high gamma dose.     

An approach to the detection of underwater remote target

An approach to the detection of underwater remote target by estimating its backscattering coefficient is presented. The key to this approach is that the echo signal is represented in state-variable model and the back-scattering coefficients of target are contained in dynamic noise of this model, thus underwater target can be detected by estimating this dynamic noise, i.e., deconvolving this model. When all noise statistics are a priori known, an optimum deconvolution algorithm based on the optimum state filter is derived, or else, an adaptive deconvolution algorithm based on the adaptive state filter of alternatively estimating the vector state and the noise statistics is developed. In the final simulation test, an echo signal with SNR equal to -6.1 dB is proceeded using the aforementioned two deconvolution algorithms, respectively, and the results demonstrate good performance of the approach.     

Discrimination of neutrons and γ-rays in liquid scintillator based on Elman neural network

In this work,a new neutron and γ(n/γ) discrimination method based on an Elman Neural Network(ENN) is proposed to improve the discrimination performance of liquid scintillator(LS) detectors.Neutron andγ data were acquired from an EJ-335 LS detector,which was exposed in a ~(241)Am-~9Be radiation field.Neutron and γ events were discriminated using two methods of artificial neural network including the ENN and a typical Back Propagation Neural Network(BPNN) as a control.The results show that the two methods have different n/γdiscrimination performances.Compared to the BPNN,the ENN provides an improved of Figure of Merit(FOM)in n/γ discrimination.The FOM increases from 0.907 ± 0.034 to 0.953 ± 0.037 by using the new method of the ENN.The proposed n/γ discrimination method based on ENN provides a new choice of pulse shape discrimination in neutron detection.