A D&T roundtable: challenges for low-power and high-performancechips

Microprocessor and other lC performance continues to improve at historic rates, with no visible end in sight for the next 10 years. However, we are starting to encounter a power wall. This is true for high-performance components as well as for low-power chips with a very limited energy budget offered by batteries. We need to find ways to manage power and energy consumption on all fronts-technology, design, and architecture-without compromising performance. Otherwise, we may face discontinuation of Moore's law for the semiconductor industry in the near future. This would be triggered not by any difficulty in the scaling of process technology but by formidable barriers posed by packaging and cooling, inefficacy of power delivery, and energy constraints dictated by battery technology, which is advancing at a very lukewarm pace     

Robust controller with disturbance rejection for hydraulic servosystems

A controller is presented that improves the performance and reduces the sensitivity of hydraulic servo systems in the presence of parameter variations, nonlinear effects, and other disturbances. The control system has enhanced closed-loop stability and can recover from steady-state and transient error quickly and completely. It consists of a servo controller, an auxiliary controller, and a robust controller. Simulation and experimental results demonstrate the validity of the controller     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

烧结直接淬火对WC－TiC－Co合金WC相微观结构及力学性能的影响

本文以ＴＥＭ和ＸＲＤ为主要手段，研究ＷＣ－ＴｉＣ－Ｃｏ硬质合金（ＹＴ１４）在直接淬火后ＷＣ相的微观结构和微观应力，比较了常规烧结态与淬火态试样ＷＣ相之间的差异，探讨了直接淬火对合金力学性能的影响。结果表明，在保持合金其他性能不降低的同时，直接淬火的抗弯强度比常规烧结提高２８％左右。并首次发现，经直接淬火热处理的ＹＴＩ４合会中与Ｃｏ相相邻的ＷＣ晶粒边界出现滑移台阶，这是淬火过程中热应力使ＷＣ晶粒内位错在｛０００１｝密排面聚集，并可能沿｛０００１｝＜１１２０＞易滑移系统强滑移的结果。直接淬火试样的微观应力比重新加热淬火的低。     

基于动态时间规整的手势加速度信号识别

为了提高基于加速度传感器的动态手势识别算法的性能,本文采用了动态时间规整(DTW)识别算法。通过该算法计算测试模板和参考模板的相似度,从而得出识别结果。为了验证该方法,建立了一套手势加速度无线采集系统,并采集了41个志愿者的手势信息。实验结果表明,该方法手势平均识别率在97%以上。与HMM识别算法相比,DTW识别算法在识别的准确率上比HMM识别算法更具优势。     

无线传感器网络中一种基于移动Sink的数据收集算法

针对移动无线传感器网络设计一种不依赖于节点地理位置的基于移动汇聚节点(Sink)的数据收集算法(Mobile Sink-based Data Gathering,MSDG)。该算法解决了无线传感器网络中多跳路由通信时出现能量空洞的"热点"问题。Sink沿途以最近的固定节点作为根节点动态构建路由树。簇内移动节点感知的数据经簇头进行数据融合计算,然后将融合后的数据沿路由树反向逐跳转发给Sink。仿真结果表明,MSDG在节点的平均能耗和网络生存时间等方面的性能远超过LEACH、ACE-L等数据收集协议。     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

Incorporating Actor-Critic in Monte Carlo tree search for symbolic regression

Neural Computing and Applications - Most traditional genetic programming methods that handle symbolic regression are random algorithms without memory and direction. They repeatedly search for the...     

A steel surface defect inspection approach towards smart industrial monitoring

Journal of Intelligent Manufacturing - With the advance in Industry 4.0, smart industrial monitoring has been proposed to timely discover faults and defects in industrial processes. Steel is widely...     

混沌信号的主要测量特性分析

初步分析了混沌信号(以Logistic为例)应用于测量中的主要特性。仿真分析了Logistic信号的频谱特性、相关特性、模糊函数。说明了混沌信号在具有较高的距离速度分辨力,同时具备强抗干扰性。对比分析了混沌码和伪随机码的多普勒容限能力。初步分析Logistic信号的抗干扰特性。