Adaptive detection of range-spread targets in homogeneous and partially homogeneous clutter plus subspace interference

Adaptive detection of range-spread targets is considered in the presence of subspace interference plus Gaussian clutter with unknown covariance matrix.The target signal and interference are supposed to lie in two linearly independent subspaces with deterministic but unknown coordinates.Relying on the two-step criteria,two adaptive detectors based on Gradient tests are proposed,in homogeneous and partially homogeneous clutter plus subspace interference,respectively.Both of the proposed detectors exhibit theoretically constant false alarm rate property against unknown clutter covariance matrix as well as the power level.Numerical results show that,the proposed detectors have better performance than their existing counterparts,especially for mismatches in the signal steering vectors.

Prediction of film ratings based on domain adaptive transfer learning

This paper examines the prediction of film ratings.Firstly,in the data feature engineering,feature construction is performed based on the original features of the film dataset.Secondly,the clustering algorithm is utilized to remove singular film samples,and feature selections are carried out.When solving the problem that film samples of the target domain are unlabelled,it is impossible to train a model and address the inconsistency in the feature dimension for film samples from the source domain.Therefore,the domain adaptive transfer learning model combined with dimensionality reduction algorithms is adopted in this paper.At the same time,in order to reduce the prediction error of models,the stacking ensemble learning model for regression is also used.Finally,through comparative experiments,the effectiveness of the proposed method is verified,which proves to be better predicting film ratings in the target domain.

Left univentricular pacing for cardiac resynchronization therapy using rate-adaptive atrioventricular delay

Objective To evaluate left univentricular （LUV） pacing for cardiac resynchronization therapy （CRT） using a rate-adaptive atrioven- tricular delay （RAAVD） algorithm to track physiological atrioventricular delay （AVD）. Methods A total of 72 patients with congestive heart failure （CHF） were randomized to RAAVD LUV pacing versus standard biventricular （BiV） pacing in a 1 ： 1 ratio. Echocardiography was used to optimize AVD for both groups. The effects of sequential BiV pacing and LUV pacing with optimized A-V （right atrio-LV） delay using an RAAVD algorithm were compared. The standard deviation （SD） of the S/R ratio in lead VI at five heart rate （HR） segments （Rs/R-SD5）, defined as the ＂tracking index,＂ was used to evaluate the accuracy of the RAAVD algorithm for tracking physiological AVD. Results TheQRS complex duration （132 ± 9.8 vs. 138± 10ms, P 〈 0.05）, the time required for optimization （21 ±5 vs. 50±8min, P〈 0.001）, the mitral regurgitant area （1.9 ± 1.1 vs. 2.5 ± 1.3 em2, P 〈 0.05）, the interventricular mechanical delay time （60.7 ± 13.3 ms vs. 68.3 ± 14.2 ms, P 〈 0.05）, and the average annual cost （13,200 ± 1000 vs. 21,600 ± 2000 RMB, P 〈 0.001） in the RAAVD LUV pacing group were significantly less than those in the standard BiV pacing group. The aortic valve velocity-time integral in the RAAVD LUV pacing group was greater than that in the standard BiV pacing group （22.7 ± 2.2 vs. 21.4 ± 2.1 cm, P 〈 0.05）. The Rs/R-SD5 was 4.08 ± 1.91 in the RAAVD LUV pacing group, and was significantly negatively correlated with improved left ventricular ejection fraction （LVEF） （ALVEF, Pearson＇s r = -0.427, P = 0.009）, and positively correlated with New York Heart Association class （Spearman＇s r - 0.348, P 0.037）. Conclusions RAAVD LUV pacing is as effective as standard BiV pacing, can be more physiological than standard BiV pacing, and can de- crease the average annual cost of CRT.

Ant Colony Optimization Based on Adaptive Volatility Rate of Pheromone Trail

Ant colony optimization (ACO) has been proved to be one of the best performing algorithms for NP-hard problems as TSP. The volatility rate of pheromone trail is one of the main parameters in ACO algorithms. It is usually set experimentally in the literatures for the application of ACO. The present paper first proposes an adaptive strategy for the volatility rate of pheromone trail according to the quality of the solutions found by artificial ants. Second, the strategy is combined with the setting of other parameters to form a new ACO method. Then, the proposed algorithm can be proved to converge to the global optimal solution. Finally, the experimental results of computing traveling salesman problems and film-copy deliverer problems also indicate that the proposed ACO approach is more effective than other ant methods and non-ant methods.

Fading Effects on the Lower Shifting of Mode Switching Thresholds in the Rate Adaptive IEEE 802.11a/g WLANs

In this paper we used the probability distribution of the average channel gain of the fading channel to analyze the degree of fading effects on both the PER (packet error rate) and the throughput in OFDM systems. Instead of solely examining the average received SNR (signal-to-noise ratio) value of a packet, considering the whole distribution of the average received SNR allows us to aggregate a better selection of the mode switching thresholds in the rate adaptive 802.11 a/g WLAN. This paper demonstrates that the set of mode switching thresholds can be determined for each individual target , so that the optimal throughput performance is obtained on a per target basis. Numerical results show that mode switching thresholds should be reduced with the lowering of target values. This conclusion could have significant implications for improving the performances of location (distance)-dependent mobile applications, since the determinations of target values are closely related to the distances between mobile devices and the access point.

RATE ADAPTIVE PROTOCOL FOR MULTIRATE IEEE 802.11 NETWORKS

In this paper, a rate adaptive protocol AMARF (Adaptive Multirate Auto Rate Fallback) for multirate IEEE 802.11 networks is proposed. In AMARF, each data rate is assigned a unique success threshold, which is a criterion to judge when to switch a rate to the next higher one, and the success thresholds can be adjusted dynamically in an adaptive manner according to the running conditions, such as packet length and channel parameters. Moreover, the proposed protocol can be implemented by software without any change to the current IEEE 802.11 standards. Simulation result shows that AMARF yields significantly higher throughput than other existing schemes including ARF and its variants, in various running conditions.

Adaptive Backstepping Control for Hypersonic Vehicles with Actuator Amplitude and Rate Saturation

This paper presents a constrained control strategy for the hypersonic vehicle with actuator amplitude,rate constraints and aerodynamic uncertainties.First,a vehicle-actuator control model is derived in consideration of actuator dynamics properties explicitly.Second,a nonlinear disturbance observer is designed to estimate the aerodynamic uncertainties,and then an adaptive backstepping control technique is adopted with a modified first-order-filter to eliminate the“explosion of terms”problem.Next,for handling the actuator amplitude and rate constraints,a novel auxiliary compensation system is constructed to generate quickly compensating signals to ensure tracking performance of command signal.By the Lyapunov stability proof,the proposed control scheme can enssure that the tracking errors converge to an arbitrarily small neighborhood around zero when the actuator constraints and aerodynamic uncertainties exist.Finally,numerical simulations are implemented to illustrate the effectiveness of the proposed control method.

Adaptive Learning Rate Optimization BP Algorithm with Logarithmic Objective Function

This paper presents an improved BP algorithm. The approach can reduce the amount of computation by using the logarithmic objective function. The learning rate μ(k) per iteration is determined by dynamic optimization method to accelerate the convergence rate. Since the determination of the learning rate in the proposed BP algorithm only uses the obtained first order derivatives in standard BP algorithm(SBP), the scale of computational and storage burden is like that of SBP algorithm,and the convergence rate is remarkably accelerated. Computer simulations demonstrate the effectiveness of the proposed algorithm

Study on rate ripple and its adaptive suppression method in inertia guidance test equipment

This paper discusses causes of the rate ripple in inertia guidance test equipment IGET, systematically analyses their effects an the rate ripple in IGTE. The analysis result shows： The rate ripple caused by the periodic errors of inductosyn and angular encoder is higher at high speed than that caused by magnetic ripple torque and friction torque, and it cannot be eliminated by adjusting control parameters of the system. And based on the nonlinear adaptive control system theory, the paper puts forward a new control system scheme to eliminate the rate ripple caused by the periodic errors of inductosyn and angular encoder, develops the adaptive control rules and makes simulation and test. Experimental result shows a significant improvement on those tables for the period disturbs under the system scheme designed. By this plan, with the input of rate 200°/s, the rate ripple falls from 5°/s to 0. 4°/s within about 6s adaptive adjustment time, being a twelfth of before adaptation, which can not be reached by common classical controls. The experimental results conform with the simulation, which proves the validity and practicability of the plan.

DESIGN ISSUES FOR BIT RATE-ADAPTIVE 3R O/E/O TRANSPONDER IN INTELLIGENT OPTICAL NETWORKS

This paper reported the design and implementation of a bit rate adaptive Optical Electronic Optical(O/E/O)transponder accomplishing almost full data rate transparency up to 2.5 Gb/s with 3R(Reamplifying,Reshaping and Retiming)processing in electronic domain.Based on the chipsets performing clock recovery in several continuous bit rate ranges,a clock and data regenerating circuit self adaptive to the bit rate of input signal was developed.Key design issues were presented,laying stress on the functional building blocks and scheme for the bit rate adaptive retiming circuit.The experimental results show a good scalability performance.

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.

Research on High Speed Communication Method of ELF-EM While Drilling Based on Adaptive Combined Filtering Algorithm

In terms of the electromagnetic wave measurement while drilling,the extremely low frequency electromagnetic(ELF-EM)signal below 20Hz is usually chosen as the downhole data carrier.To improve the transmission rate of ELF-EM signal and the signal to noise ratio(SNR)at the receiving end,the DQPSK modulation was proposed as the modulation method for the communication of electromagnetic wave system.Different from the traditional IQ orthogonal modulation and coherent demodulation methods,the proposed phase selection modulation and correlation algorithm demodulation are easier to implement and more practical.With regard to the communication synchronization,a fast algorithm,which based on the normalized cross-relation number,was used for waveform matching,and the maximum point of the correlation coefficient was used as the starting point of communication synchronization.The communication simulation results show that the proposed DQPSK modulation signal based on the adaptive combined filtering algorithm has better terminal error rate and transmission rate than the traditional modulation method.Under the same carrier frequency and code width,the transmission rate of DQPSK modulation is 4 to 5 times and 2 times that of PPM modulation and 2DPSK modulation respectively.The communication modulation and demodulation modes as well as the decoding algorithm with combined adaptive filter proposed in this paper can effectively solve practical engineering problems.

ADAPTIVE FINITE ELEMENT METHOD FOR HIGH-SPEED FLOW-STRUCTURE INTERACTION

An adaptive finite element method for high-speed flow-structure interaction is pre- sented.The cell-centered finite element method is combined with an adaptive meshing technique to solve the Navier-Stokes equations for high-speed compressible flow behavior.The energy equation and the quasi-static structural equations for aerodynamically heated structures are solved by applying the Galerkin finite element method.The finite element formulation and computational procedure are de- scribed.Interactions between the high-speed flow,structural heat transfer,and deformation are studied by two applications of Mach 10 flow over an inclined plate,and Mach 4 flow in a channel.

Adaptive coherence estimator based on the Krylov subspace technique for airborne radar

A novel adaptive detector for airborne radar space-time adaptive detection （STAD） in partially homogeneous environments is proposed. The novel detector combines the numerically stable Krylov subspace technique and diagonal loading technique, and it uses the framework of the adaptive coherence estimator （ACE）. It can effectively detect a target with low sample support. Compared with its natural competitors, the novel detector has higher proba- bility of detection （PD）, especially when the number of the training data is low. Moreover, it is shown to be practically constant false alarm rate （CFAR）.

Heartbeat and Respiration Rate Prediction Using Combined Photoplethysmography and Ballisto Cardiography

Owing to the recent trends in remote health monitoring,real-time appli-cations for measuring Heartbeat Rate and Respiration Rate(HARR)from video signals are growing rapidly.Photo Plethysmo Graphy(PPG)is a method that is operated by estimating the infinitesimal change in color of the human face,rigid motion of facial skin and head parts,etc.Ballisto Cardiography(BCG)is a non-surgical tool for obtaining a graphical depiction of the human body’s heartbeat by inducing repetitive movements found in the heart pulses.The resilience against motion artifacts induced by luminancefluctuation and the patient’s mobility var-iation is the major difficulty faced while processing the real-time video signals.In this research,a video-based HARR measuring framework is proposed based on combined PPG and BCG.Here,the noise from the input video signals is removed by using an Adaptive Kalmanfilter(AKF).Three different algorithms are used for estimating the HARR from the noise-free input signals.Initially,the noise-free sig-nals are subjected to Modified Adaptive Fourier Decomposition(MAFD)and then to Enhanced Hilbert vibration Decomposition(EHVD)andfinally to Improved Var-iation mode Decomposition(IVMD)for attaining three various results of HARR.The obtained values are compared with each other and found that the EHVD is showing better results when compared with all the other methods.

A New Two-Stage Tunable Space-Time Adaptive Detector

In order to improve the rejection capability of mismatched interferer signals,a new two-stage detector is proposed under homogeneous scenarios with unknown covariance matrix,which is obtained by cascading the adaptive matched filter(AMF)detector and the enhanced RAO(EnRAO)detector.The new detector has constant false alarm performance,and the closed-form expression of probability of false alarm and probability of detection is derived.The performance of the new detector is assessed,and analyzed in comparison with other detectors.The results show that,the proposed detector can provide enhanced rejection capability in the case of mismatch,but the performance of the detector is slightly lost under the condition of matching.

Fast Learning in Spiking Neural Networks by Learning Rate Adaptation

For accelerating the supervised learning by the SpikeProp algorithm with the temporal coding paradigm in spiking neural networks (SNNs), three learning rate adaptation methods (heuristic rule, delta-delta rule, and delta-bar-delta rule), which are used to speed up training in artificial neural networks, are used to develop the training algorithms for feedforward SNN. The performance of these algorithms is investigated by four experiments: classical XOR (exclusive or) problem, Iris dataset, fault diagnosis in the Tennessee Eastman process, and Poisson trains of discrete spikes. The results demonstrate that all the three learning rate adaptation methods are able to speed up convergence of SNN compared with the original SpikeProp algorithm. Furthermore, if the adaptive learning rate is used in combination with the momentum term, the two modifications will balance each other in a beneficial way to accomplish rapid and steady convergence. In the three learning rate adaptation methods, delta-bar-delta rule performs the best. The delta-bar-delta method with momentum has the fastest convergence rate, the greatest stability of training process, and the maximum accuracy of network learning. The proposed algorithms in this paper are simple and efficient, and consequently valuable for practical applications of SNN.

An Adaptive Approach for Hazard Regression Modeling

Regression models for survival time data involve estimation of the hazard rate as a function of predictor variables and associated slope parameters. An adaptive approach is formulated for such hazard regression modeling. The hazard rate is modeled using fractional polynomials, that is, linear combinations of products of power transforms of time together with other available predictors. These fractional polynomial models are restricted to generating positive-valued hazard rates and decreasing survival times. Exponentially distributed survival times are a special case. Parameters are estimated using maximum likelihood estimation allowing for right censored survival times. Models are evaluated and compared using likelihood cross-validation (LCV) scores. LCV scores and tolerance parameters are used to control an adaptive search through alternative fractional polynomial hazard rate models to identify effective models for the underlying survival time data. These methods are demonstrated using two different survival time data sets including survival times for lung cancer patients and for multiple myeloma patients. For the lung cancer data, the hazard rate depends distinctly on time. However, controlling for cell type provides a distinct improvement while the hazard rate depends only on cell type and no longer on time. Furthermore, Cox regression is unable to identify a cell type effect. For the multiple myeloma data, the hazard rate also depends distinctly on time. Moreover, consideration of hemoglobin at diagnosis provides a distinct improvement, the hazard rate still depends distinctly on time, and hemoglobin distinctly moderates the effect of time on the hazard rate. These results indicate that adaptive hazard rate modeling can provide unique insights into survival time data.

Throughput Analysis of IEEE 802.11 Multirate WLANs with Collision Aware Rate Adaptation Algorithm

This paper presents a mathematical model that analyzes the throughput of the IEEE 802.11b distributed coordination function （DCF） with the collision aware rate adaptation （CARA） algorithm. IEEE 802.11 WLANs provide multiple transmission rates to improve system throughput by adapting the transmission rate to the current channel conditions. The system throughput is determined by some stations using low transmission rates due to bad channel conditions. CARA algorithm does not disturb the existing IEEE 802.11b formats and it can be easily incorporated into the commercial wireless local area networks （WLAN） devices. Finally, we verify our findings with simulation.