Constant False Alarm Rate Acquisition Algorithm for Compass B1C Signal

In order to improve the sensitivity of the Compass B1C signal acquisition for the receiver,the principle of constant false alarm rate(CFAR)is applied for the B1C pilot channel acquisition to realize the dynamic adjustment of the threshold of acquisition against the carrier to noise ratio.The non-coherent data/pilot combined acquisition algorithm for B1C signal is analyzed to make full use of the power of the B1C signal under the condition of low carrier to noise ratio.On this basis,to improve the acquisition sensitivity of the receiver,the principle of constant false alarm probability is applied for the non-coherent data/pilot combined acquisition algorithm.Theoretical analysis and simulations show that the non-coherent data/pilot combined acquisition algorithm with CFAR improves the B1C signal acquisition sensitivity of the receiver significantly,and achieves a better Receiver Operating Characteristic compared with the traditional acquisition algorithms.

Early detection of sudden cardiac death by using classical linear techniques and time-frequency methods on electrocardiogram signals

Early detection of sudden cardiac death may be used for surviving the life of cardiac patients. In this paper we have investigated an algorithm to detect and predict sudden cardiac death, by processing of heart rate variability signal through the classical and time-frequency methods. At first, one minute of ECG signals, just before the cardiac death event are extracted and used to compute heart rate variability (HRV) signal. Five features in time domain and four features in frequency domain are extracted from the HRV signal and used as classical linear features. Then the Wigner Ville transform is applied to the HRV signal, and 11 extra features in the time-frequency (TF) domain are obtained. In order to improve the performance of classification, the principal component analysis (PCA) is applied to the obtained features vector. Finally a neural network classifier is applied to the reduced features. The obtained results show that the TF method can classify normal and SCD subjects, more efficiently than the classical methods. A MIT-BIH ECG database was used to evaluate the proposed method. The proposed method was implemented using MLP classifier and had 74.36% and 99.16% correct detection rate (accuracy) for classical features and TF method, respectively. Also, the accuracy of the KNN classifier were 73.87% and 96.04%.

A new method for improving the inductively coupled data transmission rate of mooring buoy based on carrier signal frequency selection

In the inductively coupled data transmission system of the mooring buoy, the carrier signal frequency of the transmission channel is limited due to the inherent characteristics of the system, resulting in limited channel bandwidth. The limited channel bandwidth limits the increase in inductively coupled data transmission rate.In order to improve the inductively coupled data transmission rate of mooring buoy as much as possible without damaging the data transmission performance, a new method was proposed in this paper. The method is proposed to improve the data transmission rate by selecting the appropriate carrier signal frequencies based on the principle of maximizing the amplitude value of amplitude-frequency characteristic curve of the system. Research has been done according to this method as follows. Firstly, according to the inductively coupled transmission mooring buoy structure, the inductively coupled data transmission circuit model was established. The binary frequency shift keying(2FSK) digital signal modulation mode was selected. Through theoretical analysis, the relation between the carrier signal frequency and the data transmission performance, the relation between the carrier signal frequency and the 2FSK signal bandwidth were obtained. Secondly, the performance and the bandwidth of the signal transmission were studied for the inherent characteristics of the actual inductively coupled data transmission system. The amplitude-frequency characteristic of the system was analyzed by experiments. By selecting the appropriate carrier signal frequency parameters, an excellent data transmission performance was guaranteed and a large 2FSK signal bandwidth was obtained. Finally, an inductively coupled data transmission rate optimization experiment and a bit error rate analysis experiment were designed and carried out. The results show that the high-speed and reliable data transmission of the system was realized and the rate can reach 100 kbps.

Vibration Signals and Condition Monitoring for Wind Turbines

Rolling element bearings are critical parts of modern wind turbines as they carry the loads of the turning structure and the wind force. The stochastic nature of the wind loads makes it difficult to estimate the useful operational life of the bearings. Condition monitoring of these bearings in a real time environment could be very helpful in estimating their performance and in scheduling maintenance actions when a condition-based maintenance strategy is followed. This procedure can be successfully implemented by using vibration analysis in the time domain or in the frequency domain, giving useful results about the current condition of bearings and the location of potential faults. Permanently located transducers on proper positions on the bearings’ housings can be used in order to collect, process and evaluate real time measurements and provide information about the bearing’s performance. In this work, a test rig is utilized in order to evaluate the performance of rolling bearings. The results of the experimentation are satisfactory and the progress of fatigue failures can be predicted through vibration analysis techniques showing that implementation in real scale may be useful.

Chirp-Rate Resolution of Fractional Fourier Transform in Multi-component LFM Signal

Distinguishing close chirp-rates of different linear frequency modulation （LFM） signals under concentrated and complicated signal environment was studied. Firstly, detection and parameter estimation of multi-component LFM signal were used by discrete fast fractional Fourier transform （FrFT）. Then the expression of chirp-rate resolution in fractional Fourier domain （FrFD） was deduced from discrete normalize time-frequency distribution, when multi-component LFM signal had only one center frequency. Furthermore, the detail influence of the sampling time, sampling frequency and chirp-rate upon the resolution was analyzed by partial differential equation. Simulation results and analysis indicate that increasing the sampling time can enhance the resolution, but the influence of the sampling frequency can he omitted. What＇s more, in multi-component LFM signal, the chirp-rate resolution of FrFT is no less than a minimal value, and it mainly dependent on the biggest value of chirp-rates, with which it has an approximately positive exponential relationship.

Parameter Estimation of Linear Frequency Modulated Signals Based on Holder Coefficient

The current parameter estimation algorithms of chirp rate have high complexity and long calculation time,meantime they are difficult to achieve high estimation rate. Therefore,in order to overcome these problems,in this paper,a new parameter estimation algorithm based on Holder coefficient is presented. Firstly,this algorithm calculates the correlation curve of the Holder coefficient value under different chirp rate. Secondly,this algorithm calculates the correlation curve under different SNR. Finally,the fitting curve expression can be got by the correlation curve,and then the estimation value of chirp rate can also be got. The theory analysis and simulation results show that this algorithm is simple and easy to realize,and has much better application value for real-time estimation.

Enhanced quadrature signaling-based cooperative transmission with full rate and full diversity

Quadrature signaling-based cooperative transmission is an efficient and simple scheme to obtain spatial diversity.However,this scheme causes date rate loss compared with direct transmission.In this work,our focus is on recovering from the data rate loss while simultaneously achieving spatial diversity.Particularly,an enhanced quadrature signaling-based cooperative scheme was designed,which can realize full-rate transmission by using the signal space diversity(SSD)technique.Then,accurate bit error rate(BER)expression for the full-rate scheme was derived over independent and non-identically distributed(INID)Rayleigh fading channels.Specifically,a closed-form BER expression is obtained,which is quite tight over the whole SNR range,and thus allows for rapid and efficient evaluation of system performance under various channel conditions.Moreover,an asymptotic approximation of the BER was derived to show that the full-rate scheme can achieve full diversity.Simulation results verify the tightness of the analysis and show that the full-rate scheme significantly outperforms the traditional quadrature signaling-based scheme by about 2 dB with the same complexity order.

Finite rate of innovation sparse sampling for a binary frequency-coded ultrasonic signal

To achieve sparse sampling on a coded ultrasonic signal,the finite rate of innovation(FRI)sparse sampling technique is proposed on a binary frequency-coded(BFC)ultrasonic signal.A framework of FRI-based sparse sampling for an ultrasonic signal pulse is presented.Differences between the pulse and the coded ultrasonic signal are analyzed,and a response mathematical model of the coded ultrasonic signal is established.A time-domain transform algorithm,called the high-order moment method,is applied to obtain a pulse stream signal to assist BFC ultrasonic signal sparse sampling.A sampling of the output signal with a uniform interval is then performed after modulating the pulse stream signal by a sampling kernel.FRI-based sparse sampling is performed using a self-made circuit on an aluminum alloy sample.Experimental results show that the sampling rate reduces to 0.5 MHz,which is at least 12.8 MHz in the Nyquist sampling mode.The echo peak amplitude and the time of flight are estimated from the sparse sampling data with maximum errors of 9.324%and 0.031%,respectively.This research can provide a theoretical basis and practical application reference for reducing the sampling rate and data volume in coded ultrasonic testing.

BER Performance of Finite in Time Optimal FTN Signals for the Viterbi Algorithm

In this article, we consider the faster than Nyquist(FTN) technology in aspects of the application of the Viterbi algorithm(VA). Finite in time optimal FTN signals are used to provide a symbol rate higher than the "Nyquist barrier" without any encoding. These signals are obtained as the solutions of the corresponding optimization problem. Optimal signals are characterized by intersymbol interference(ISI). This fact leads to significant bit error rate(BER) performance degradation for "classical" forms of signals. However, ISI can be controlled by the restriction of the optimization problem. So we can use optimal signals in conditions of increased duration and an increased symbol rate without significant energy losses. The additional symbol rate increase leads to the increase of the reception algorithm complexity. We consider the application of VA for optimal FTN signals reception. The application of VA for receiving optimal FTN signals with increased duration provides close to the potential performance of BER,while the symbol rate is twice above the Nyquist limit.

Novel Sampling and Reconstruction Method for Non-Bandlimited Impulse Signals

To sample non-bandlimited impulse signals, an extremely high-sampling rate analog-todigital converters （ADC） is required. Such an ADC is very difficult to be implemented with present semiconductor technology. In this paper, a novel sampling and reconstruction method for impulse signals is proposed. The required sampling rate of the proposed method is close to the signal innovation rate, which is much lower than the Nyquist rate in conventional Shannon sampling theory. Analysis and simulation results show that the proposed method can achieve very good reconstruction performance in the presence of noise.

The Signal Extraction of Fetal Heart Rate Based on Wavelet Transform and BP Neural Network

This paper briefly introduces the collection and recognition of bio-medical sig nals, designs the method to collect FM signals. A detailed discussion on the sys tem hardware, structure and functions is also given. Under LabWindows/CVI,the ha rdware and the driver do compatible, the hardware equipment work properly active ly. The paper adopts multi threading technology for real-time analysis and make s use of latency time of CPU effectively, expedites program reflect speed, impro ve s the program to perform efficiency. One threading is collecting data; the other threading is analyzing data. Using the method, it is broaden to analyze the sig nal in real-time. Wavelet transform to remove the main interference in the FM a nd by adding time-window to recognize with BP network; Finally the results of c ollecting signals and BP networks are discussed.8 pregnant women’s signals of F M were collected successfully by using the sensor. The correct of BP network rec ognition is about 83.3% by using the above measure.

Physiological signal processing in heart rate variability measurement:A focus on spectral analysis

Human physiological(biological)systems function in such a way that their complexity requires mathematical analysis.The functioning of the brain,heart and other parts are so complex to be easily comprehended.Under conditions of rest or work,the temporal distances of successive heartbeats are subject to fluctuations,thereby forming the basis of Heart Rate Variability(HRV).In normal conditions,the human is persistently exposed to highly changing and dynamic situational demands.With these demands in mind,HRV can,therefore,be considered as the human organism’s ability to cope with and adapt to continuous situational requirements,both physiologically and emotionally.Fast Fourier Transform(FFT)is used in various physiological signal processing,such as heart rate variability.FFT allows a spectral analysis of HRV and is great help in HRV analysis and interpretation.

Carrier frequency and symbol rate estimation based on cyclic spectrum

Carrier frequency and symbol rate estimation are the main contents of parameter estimation,which is the basis of modulation recognition and further processing of signals especially in non-cooperative communication.With the development of wireless communication,the signal transmission environment has become increasingly bad,causing more difficulties in parameter estimation.It is well known that the signal cycle spectrum is robust to noises and signal parameters are closely related.In practice,it is impossible to calculate the cyclic spectrum of infinite length data signals.When using finite length data to obtain a cycle spectrum,the truncation noise is induced,resulting in interference.It is necessary to overcome the influence of noises in order to improve the detection ability of discrete spectral lines.An improved method of the discrete spectral line extraction algorithm is proposed by reflecting the amplitude advantage of discrete spectral lines through salient features of continuous noises in discrete spectral line neighborhood.

Omega-3 polyunsaturated fatty acids promote liver regeneration after 90% hepatectomy in rats

AIM:To evaluate the effectiveness of omega-3 polyunsaturated fatty acid(ω-3 PUFA) administration on liver regeneration after 90% partial hepatectomy(PH) in rats.METHODS:ω-3 PUFAs were intravenously injected in the ω-3 PUFA group before PH surgery.PH,sparing only the caudate lobe,was performed in both the control and the ω-3 PUFA group.Survival rates,liver weight/body weight ratios,liver weights,HE staining,transmission electron microscope imaging,nuclearassociated antigen Ki-67,enzyme-linked immunosorbent assay and signal transduction were evaluated to analyze liver regeneration.RESULTS:All rats in the control group died within 30 h after hepatectomy.Survival rates in the ω-3 PUFA group were 20/20 at 30 h and 4/20 1 wk after PH.Liver weight/body weight ratios and liver weights increased significantly in the ω-3 PUFA group.The structure of sinusoidal endothelial cells and space of Disse was greatly restored in the ω-3 PUFA group compared to the control group after PH.In the ω-3 PUFA group,interleukin(IL)-4 and IL-10 levels were significantly increased whereas IL-6 and tumor necrosis factor-levels were dramatically decreased.In addition,activation of protein kinase B(Akt) and of signal transducer and activator of transcription 3 signaling pathway were identified at an earlier time after PH in the ω-3 PUFA group.CONCLUSION:Omega-3 polyunsaturated fatty acids may prevent acute liver failure and promote liver regeneration after 90% hepatectomy in rats.

Bistable Stochastic Resonance Enhanced 4-ary PAM Signal Detection under Low SNR

To boost the performance of 4-ary pulse amplitude modulated(PAM) at low signal-to-noise ratio(SNR), bistable stochastic resonance(BSR) system is introduced into digital communications system and get a reliable signal detection scheme. In this paper, we first analyse BSR system for different amplitudes of 4-ary PAM signals. The steadystate of the bistable system will be statistically distinct, and the feasibility of the proposed detection scheme is confirmed. On this basis, we present a detailed study on steady-state transitions of the BSR system, and an explicit expression of the bistable system parameters is derived. By setting the bistable system parameters, bistable system, 4-ary PAM signal, and noise reach the resonance state, and the BSR-based detection scheme is implemented. Moreover, we derive an analytical expression to calculate the symbol error rate(SER) of 4-ary PAM signals with the BSR-based detection under additive white Gaussian noise(AWGN). Finally, the simulation results validate that BSR-based detection scheme can improve the detection performance while efficiently reducing the symbol error rate.

Quick System-Level DDR3 Signal Integrity Simulation Research

---Double data rate synchronous dynamic random access memory （DDR3） has become one of the most mainstream applications in current server and computer systems. In order to quickly set up a system-level signal integrity （SI） simulation flow for the DDR3 interface, two system-level SI simulation methodologies, which are board-level S-parameter extraction in the frequency-domain and system-level simulation assumptions in the time domain, are introduced in this paper. By comparing the flow of Speed2000 and PowerSI/Hspice, PowerSI is chosen for the printed circuit board （PCB） board-level S-parameter extraction, while Tektronix oscilloscope （TDS7404） is used for the DDR3 waveform measurement. The lab measurement shows good agreement between simulation and measurement. The study shows that the combination of PowerSI and Hspice is recommended for quick system-level DDR3 SI simulation.

Human Respiration Rate Estimation Using Ultra-wideband Distributed Cognitive Radar System

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare,rescue,and security applications.In this paper,we first present a multi-ray propagation model for UWB signal,which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces,A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment.This model enables replication of time-varying multipath profiles due to the displacement of a human chest.Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate.The analytical framework can serve as a basis in the planning and evaluation of future rheasurement programs.We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture.

Study on Real-Time Heart Rate Detection Based on Multi-People

Heart rate is an important vital characteristic which indicates physical and mental health status.Typically heart rate measurement instruments require direct contact with the skin which is time-consuming and costly.Therefore,the study of non-contact heart rate measurement methods is of great importance.Based on the principles of photoelectric volumetric tracing,we use a computer device and camera to capture facial images,accurately detect face regions,and to detect multiple facial images using a multi-target tracking algorithm.Then after the regional segmentation of the facial image,the signal acquisition of the region of interest is further resolved.Finally,frequency detection of the collected Photo-plethysmography(PPG)and Electrocardiography(ECG)signals is completed with peak detection,Fourier analysis,and a Waveletfilter.The experimental results show that the subject’s heart rate can be detected quickly and accurately even when monitoring multiple facial targets simultaneously.

Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

In this study,single-channel photoplethysmography(PPG)signals were used to estimate the heart rate(HR),diastolic blood pressure(DBP),and systolic blood pressure(SBP).A deep learning model was proposed using a long-term recurrent convolutional network(LRCN)modified from a deep learning algorithm,the convolutional neural network model of the modified inception deep learning module,and a long short-term memory network(LSTM)to improve the model’s accuracy of BP and HR measurements.The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository.How to design a filter of PPG signals and how to choose the loss functions for deep learning model were also discussed in the study.Finally,the stability of the proposed model was tested using a 10-fold cross-validation,with an MAE±SD of 2.942±5.076 mmHg for SBP,1.747±3.042 mmHg for DBP,and 1.137±2.463 bpm for the HR.Compared with its existing counterparts,the model entailed less computational load and was more accurate in estimating SBP,DBP,and HR.These results established the validity of the model.