Noise cancellation of a multi-reference full-wave magnetic resonance sounding signal based on a modified sigmoid variable step size least mean square algorithm

Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.

Novel LMS adaptive filtering algorithm with variable step size

By analyzing algorithms available for variable step size least mean square(LMS)adaptive filter,a new modified LMS adaptive filtering algorithm with variable step size is proposed,along with performance analysis based on different parameters.Compared with the existing algorithms through the simulation,the proposed algorithm has faster convergence speed and smaller steady state error.

New Hybrid Parallel Algorithm for Variable-sized Batch Splitting Scheduling with Alternative Machines in Job Shops

The batch splitting scheduling problem has recently become a major target in manufacturing systems, and the researchers have obtained great achievements, whereas most of existing related researches focus on equal-sized and consistent-sized batch splitting scheduling problem, and solve the problem by fixing the number of sub-batches, or the sub-batch sizes, or both. Under such circumstance and to provide a practical method for production scheduling in batch production mode, a study was made on the batch splitting scheduling problem on alternative machines, based on the objective to minimize the makespan. A scheduling approach was presented to address the variable-sized batch splitting scheduling problem in job shops trying to optimize both the number of sub-bathes and the sub-batch sizes, based on differential evolution（DE）, making full use of the finding that the sum of values of genes in one chromosome remains the same before and after mutation in DE. Considering before-arrival set-up time and processing time separately, a variable-sized batch splitting scheduling model was established and a new hybrid algorithm was brought forward to solve both the batch splitting problem and the batch scheduling problem. A new parallel chromosome representation was adopted, and the batch scheduling chromosome and the batch splitting chromosome were treated separately during the global search procedure, based on self-adaptive DE and genetic crossover operator, respectively. A new local search method was further designed to gain a better performance. A solution consists of the optimum number of sub-bathes for each operation per job, the optimum batch size for each sub-batch and the optimum sequence of sub-batches. Computational experiments of four test instances and a realistic problem in a speaker workshop were performed to testify the effectiveness of the proposed scheduling method. The study takes advantage of DE＇s distinctive feature, and employs the algorithm as a solution approach, and thereby deepens and enriches the content of batch splitting scheduling.

Active micro-vibration control based on improved variable step size LMS algorithm

The contradiction of variable step size least mean square(LMS)algorithm between fast convergence speed and small steady-state error has always existed.So,a new algorithm based on the combination of logarithmic and symbolic function and step size factor is proposed.It establishes a new updating method of step factor that is related to step factor and error signal.This work makes an analysis from 3 aspects:theoretical analysis,theoretical verification and specific experiments.The experimental results show that the proposed algorithm is superior to other variable step size algorithms in convergence speed and steady-state error.

Effect of some operational variables on bubble size in a pilot-scale mechanical flotation machine

This work aims to provide a relationship of how the key operational variables of frother type and impeller speed affect the size of bubble(D32). The study was performed using pilot-scale equipment(0.8 m3) that is up to two orders of magnitude larger than equipment used for studies performed to date by others, and incorporated the key process variables of frother type and impeller speed. The results show that each frother family exhibits a unique CCC95-HLB relationship dependent on n(number of C-atoms in alkyl group) and m(number of propylene oxide group). Empirical models were developed to predict CCC95 from HLB associated with other two parameters α and β. The impeller speed-bubble size tests show that D32 is unaffected by increased impeller tip speed across the range of 4.6 to 9.2 m/s(representing the industrial operating range), although D32 starts to increase below 4.6 m/s. The finding is valid for both coalescing and non-coalescing conditions. The results suggest that the bubble size and bubble size distribution(BSD) being created do not change with increasing impeller speed in the quiescent zone of the flotation.

Finite-size analysis of continuous-variable quantum key distribution with entanglement in the middle

Continuous-variable quantum key distribution(CVQKD) protocols with entanglement in the middle(EM) enable long maximal transmission distances for quantum communications. For the security analysis of the protocols, it is usually assumed that Eve performs collective Gaussian attacks and there is a lack of finite-size analysis of the protocols. However,in this paper we consider the finite-size regime of the EM-based CVQKD protocols by exposing the protocol to collective attacks and coherent attacks. We differentiate between the collective attacks and the coherent attacks while comparing asymptotic key rate and the key rate in the finite-size scenarios. Moreover, both symmetric and asymmetric configurations are collated in a contrastive analysis. As expected, the derived results in the finite-size scenarios are less useful than those acquired in the asymptotic regime. Nevertheless, we find that CVQKD with entanglement in the middle is capable of providing fully secure secret keys taking the finite-size effects into account with transmission distances of more than 30 km.

Fast Approaches for Sub-pixel Precision Variable Block Size Motion Estimation

The new features of H. 264 video coding standard make the motion estimation module much more time consuming than before. Especially, the motion search is required for each of the 4 modes for inter prediction. In order to reduce the computational complexity, we analyze the statistics of results of motion estimation, such as the continuity of best modes of blocks in successive frames and the chance to give up a sub-partition mode （smaller than 16 × 16） after integer-pixel motion estimation, from which we suggest to make mode prediction based on the motion information of the previous frame and skip sub-pixel motion estimation in subpartition mode selectively. According to the experimental result, the proposed algorithm can save 75 % of the computational time with a slight degradation （0.03 dB） on PSNR compared with the pseudocode of fast search motion estimation in JM12.2.

Small and Mid-Size Pump-Turbines with Variable Speed

The stability of the grid is jeopardized with the large percentage of non-dispatchable renewables like wind power and also with increasing solar power. This creates various problems because these forms of energy are very volatile and difficult to predict. In most countries the in-feed of these sources must not be curtailed. In addition most of the renewables do not provide short circuit capacity and inertia in the same way as classical units and so further worsen the stability of the grid. The growing exploitation of wind and solar might be limited due to grid stability problems. In order to compensate those problems a large amount of reserve capacity is needed and therefore new technologies for electricity storage are required. Hydraulic pumped storage—the classical storage technology—has some disadvantages. These plants are in mountain regions often far away from wind farms. The distance to the wind farms mean additional loading for the already stressed grid and additional transmission losses. To compensate the very volatile wind energy, the pump input power should be varied continuously. This is so far only possible with variable speed units. Up to now double-fed asynchronous motor-generators are used which are rather expensive. In order to provide a solution for the described situation, ANDRITZ HYDRO has developed a new innovative concept of decentralized pump storage plants. Small standardized pump turbines are combined with a synchronous motor-generator and a full size converter which allows speed variation in pump and turbine mode over a wide range. These plants can be built locally close to wind farms and other sources to be balanced, allowing the increase of renewable energy without increasing the transmission line capacity. For the future smart grids this will be a key storage technology. This concept is reliable, innovative and more economic than other storage technologies.

Joint receiving mechanism based on blind equalization with variable step size for M-QAM modulation

The problem of inter symbol interference（ ISI） in wireless communication systems caused by multipath propagation when using high order modulation like M-Q AMis solved. Since the wireless receiver doesn＇t require a training sequence,a blind equalization channel is implemented in the receiver to increase the throughput of the system. To improve the performances of both the blind equalizer and the system,a joint receiving mechanismincluding variable step size（ VSS） modified constant modulus algorithms（ MC-MA） and modified decision directed modulus algorithms（ MD DMA） is proposed to ameliorate the convergence speed and mean square error（ MSE） performance and combat the phase error when using high order QAM modulation. The VSS scheme is based on the selection of step size according to the distance between the output of the equalizer and the desired output in the constellation plane. Analysis and simulations showthat the performance of the proposed VSS-MCMA-MD DMA mechanismis better than that of algorithms with a fixed step size. In addition,the MCMA-MDDMA with VSS can performthe phase recovery by itself.

Study of Variable Step Size LMS Adaptive Algorithm Based on Variable Region

This paper puts forward a new variable step size LMS adaptive algorithm based on variable region. The step size μ(k) in the algorithm varies with the variation of the region of deviation e(k) to ensure the optimization of the three performance objectives including initial convergent speed, trace ability of the time-varying system and steady disregulation. The paper demonstrates the convergence of the algorithm accompanied by random noise.

Finite-size analysis of eight-state continuous-variable quantum key distribution with the linear optics cloning machine

We propose a method to improve the secret key rate of an eight-state continuous-variable quantum key distribution（CVQKD） by using a linear optics cloning machine（LOCM）. In the proposed scheme, an LOCM is exploited to compensate for the imperfections of Bob＇s apparatus, so that the generated secret key rate of the eight-state protocol could be well enhanced. We investigate the security of our proposed protocol in a finite-size scenario so as to further approach the practical value of a secret key rate. Numeric simulation shows that the LOCM with reasonable tuning gain λ and transmittance τcan effectively improve the secret key rate of eight-state CVQKD in both an asymptotic limit and a finite-size regime.Furthermore, we obtain the tightest bound of the secure distance by taking the finite-size effect into account, which is more practical than that obtained in the asymptotic limit.

Derivation of Optimal Global Equalization Function with Variable Size Block Based Local Contrast Enhancement

因为图象质量和对比改进是图象特征 largely.And 上的 depndent ，常规全球对比改进是困难的在各种各样的图象适用本地对比改进不仅引起褪色的效果，而且 blocks.To 解决这些缺点，这份报纸与可变尺寸块导出最佳的全球均等功能最佳的均等功能使它成为的基于的本地对比 enhancement.The

Finite-difference modeling with variable grid-size and adaptive time-step in porous media

Forward modeling of elastic wave propagation in porous media has great importance for understanding and interpreting the influences of rock properties on characteristics of seismic wavefield. However,the finite-difference forward-modeling method is usually implemented with global spatial grid-size and time-step; it consumes large amounts of computational cost when small-scaled oil/gas-bearing structures or large velocity-contrast exist underground. To overcome this handicap,combined with variable grid-size and time-step,this paper developed a staggered-grid finite-difference scheme for elastic wave modeling in porous media. Variable finite-difference coefficients and wavefield interpolation were used to realize the transition of wave propagation between regions of different grid-size. The accuracy and efficiency of the algorithm were shown by numerical examples. The proposed method is advanced with low computational cost in elastic wave simulation for heterogeneous oil/gas reservoirs.

Bounded space algorithms for variant of variable-sized bin packing

Given a list of items and a sequence of variable-sized bins arriving one by one, it is NP-hard to pack the items into the bin list with a goal to minimize the total size of bins from the earliest one to the last used. In this paper a set of approximation algorithms is presented for cases in which the ability to preview at most k(>=2) arriving bins is given. With the essential assumption that all bin sizes are not less than the largest item size, analytical results show the asymptotic worst case ratios of all k-bounded space and offline algorithms are 2. Based on experiments by applying algorithms to instances in which item sizes and bin sizes are drawn independently from the continuous uniform distribution respectively in the interval [0,u] and [u,1], average- case experimental results show that, with fixed k, algorithms with the Best Fit packing(closing) rule are statistically better than those with the First Fit packing(closing) rule.

Design of digital calibration based on variable step size of sub-binary SAR ADC

Addressing the impact of capacitor mismatch on the conversion accuracy of successive approximation register analog-to-digital converter(SAR ADC),a 12-bit 1 MS/s sub-binary SAR ADC designed using variable step size digital calibration was proposed.The least mean square(LMS)calibration algorithm was employed with a ramp signal used as the calibration input.Weight errors,extracted under injected disturbances,underwent iterative training to optimize weight values.To address the trade-off between conversion accuracy and speed caused by a fixed step size,a novel variable step size algorithm tailored for SAR ADC calibration was proposed.The core circuit and layout of the SAR ADC were implemented using the Taiwan Semiconductor Manufacturing Company(TSMC)0.35μm complementary metal-oxide-semiconductor(CMOS)commercial process.Simulation of the SAR ADC calibration algorithm was conducted using Simulink,demonstrating quick convergence and meeting conversion accuracy requirements compared to fixed step size simulation.The results indicated that the convergence speed of the LMS digital calibration algorithm with variable step size was approximately eight times faster than that with a fixed step size,also yielding a lower mean square error(MSE).After calibration,the simulation results for the SAR ADC exhibited an effective number of bit(ENOB)of 11.79 bit and a signal-to-noise and distortion ratio(SNDR)of 72.72 dB,signifying a notable enhancement in the SAR ADC performance.

New normalized LMS adaptive filter with a variable regularization factor

A new normalized least mean square(NLMS) adaptive filter is first derived from a cost function, which incorporates the conventional one of the NLMS with a minimum-disturbance(MD)constraint. A variable regularization factor(RF) is then employed to control the contribution made by the MD constraint in the cost function. Analysis results show that the RF can be taken as a combination of the step size and regularization parameter in the conventional NLMS. This implies that these parameters can be jointly controlled by simply tuning the RF as the proposed algorithm does. It also demonstrates that the RF can accelerate the convergence rate of the proposed algorithm and its optimal value can be obtained by minimizing the squared noise-free posteriori error. A method for automatically determining the value of the RF is also presented, which is free of any prior knowledge of the noise. While simulation results verify the analytical ones, it is also illustrated that the performance of the proposed algorithm is superior to the state-of-art ones in both the steady-state misalignment and the convergence rate. A novel algorithm is proposed to solve some problems. Simulation results show the effectiveness of the proposed algorithm.

Evaluation of a Pulse Width Modulated Bypass Nozzle for the Development of a Variable Load Residential Oil Burner

Due to the need for energy conservation in buildings and the simultaneous benefit of cost savings, the development of a low firing rate load modulating residential oil burner is very desirable. One of the two main requirements of such a burner is the development of a burner nozzle that is able to maintain the particle size distribution of the fuel spray in the desirable (small) size range for efficient and stable combustion. The other being the ability to vary the air flow rate and air distribution around the fuel nozzle in the burner for optimal combustion at the current fuel firing rate. In this paper, which deals with the first requirement, we show that by using pulse width modulation in the bypass channel of a commercial off-the-shelf bypass nozzle, this objective can be met. Here we present results of spray patterns and particle size distribution for a range of fuel firing rates. The results show that a desirable fuel spray pattern can be maintained over a fuel firing rate turndown ratio (Maximum Fuel Flow Rate/Minimum Fuel Flow Rate) of 3.7. Thus here we successfully demonstrate the ability to electronically vary the fuel firing rate by more than a factor of 3 while simultaneously maintaining good atomization.

Criticality in Two-Variable Earthquake Model on a Random Graph

A two-variable earthquake model on a quenched random graph is established here.It can be seen as a generalization of the OFC models.We numerically study the critical behavior of the model when the system is nonconservative:the result indicates that the model exhibits self-organized criticality deep within the nonconservative regime.The probability distribution for avalanche size obeys finite size scaling.We compare our model with the model introduced by Stefano Lise and Maya Paczuski [Phys.Rev.Lett.88 (2002) 228301],it is proved that they are not in the same universality class.

基于RRT^(*)-DR算法的机械臂避障路径规划

为使机械臂在障碍物环境下快速规划较优路径,提出了一种基于动态区域采样的改进RRT^(*)-DR路径规划算法,将整个规划过程分为快速探索路径和优化初始路径两个步骤。首先利用半目标导向扩展快速探索,找到连接起始点和目标点的路径。随后利用动态区域采样方法,始终在当前最优路径的周边范围内采样,优先密化当前最优路径附近的节点树,节省计算资源,使初始路径经过迭代快速向渐进最优路径收敛。同时,提出一种近障碍节点变步长机制,有选择性地缩短靠近障碍节点的扩展步长,可有效减少碰撞检测失败次数,提高算法效率。最后,在MATLAB和ROS系统下进行路径规划算法仿真,结果表明RRT^(*)-DR算法可在更短时间内实现路径规划,同时有效缩小路径代价。进一步通过实体机器人路径规划避障实验,验证了该算法的实用性和有效性。

基于功率预测的自适应变步长MPPT算法研究

最大功率点跟踪技术(Maximum Power Point Tracking, MPPT)是光伏发电系统中关键技术研究的热点之一。针对传统扰动观察法跟踪速度和精度无法兼顾的问题,文中提出了一种以功率变化量为步长控制量的自适应变步长扰动观察法,通过判断功率变化趋势,对远离最大功率点,采用大步长逼近;靠近最大功率点,采用小步长逼近。建立太阳能光伏电池数学模型得到其输出特性曲线,再利用MATLAB/Simulink搭建基于Boost电路的MPPT仿真模型,最后经仿真验证了所提出算法的稳定性、快速性和准确性,它比传统算法具有更好的MPPT暂态性能。