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.

Towards frequency adaptation for delayed feedback deep brain stimulations

In neurodegenerative disorders such as Parkinson＇s disease （PD）, deep brain stimulation （DBS） is a desirable approach when the medication is less effective for treating the symptoms. DBS incorporates transferring electrical pulses to a specific tissue of the central nervous system, obtaining therapeutic results by modulating the neuronal activity of that region. DBS has certain advantages such as reversibility and adjustability features over medication, since the neuronal firing patterns can be recorded and used to alter the parameters of the DBS signal （Benabid et al., 2009）. One of the DBS indications is its ability to suppress the abnormal neuronal activity to treat symptoms like tremor, akinesia and dystonia.

Cluster projective synchronization of complex networks with nonidentical dynamical nodes

We investigate a new cluster projective synchronization （CPS） scheme in time-varying delay coupled complex dynamical networks with nonidentical nodes. Based on the community structure of the networks, the controllers are designed differently for the nodes in one community, which have direct connections to the nodes in the other communities and the nodes without direct connections to the nodes in the other communities. Some sufficient criteria are derived to ensure the nodes in the same group projectively synchronize and there is also projective synchronization between nodes in different groups. Particularly, the weight configuration matrix is not assumed to be symmetric or irreducible. The numerical simulations are performed to verify the effectiveness of the theoretical results.

Study on moving target detection to passive radar based on FM broadcast transmitter

Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field. First of all, direct-path interference （DPI） suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation（FM） broadcast transmitter is analyzed in this article; Secondly, a space-time-frequency domain synthetic solution to this problem is introduced： Adaptive nulling array processing is considered in the space domain, DPI cancellation based on adaptive fractional delay interpolation （AFDI） technique is used in planned time domain, and long-time coherent integration is utilized in the frequency domain; Finaily, an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator, Simulation results by real collected data show that the proposed method has a better performance of moving target detection.

Model Reference Adaptive Control for Networked Distributed Systems with Strong Interconnections and Communication Delays

In recent years, networked distributed control systems（NDCS） have received research attention. Two of the main challenges that such systems face are possible delays in the communication network and the effect of strong interconnections between agents. This paper considers an NDCS that has delays in the communication network, as well as strong interconnections between its agents. The control objective is to make each agent track efficiently a reference model by attenuating the effect of strong interconnections via feedback based on the delayed information. First, the authors assume that each agent knows its own dynamics, as well as the interconnection parameters, but receives information about the states of its neighbors with some communication delay. The authors propose a distributed control scheme and prove that if the interconnections can be weakened and if the communication delays are small enough, then the proposed scheme guarantees that the tracking error of each agent is bounded with a bound that depends on the size of the weakened interconnections and delays, and reduces to zero as these uncertainties reduce to zero. The authors then consider a more realistic situation where the interconnections between agents are unknown despite the cooperation and sharing of state information. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense with respect to the size of the weakened interconnections and delays, provided the weakened interconnections and time delays are small enough. The authors then consider the case that each agent knows neither its dynamics nor the interconnection matrices. For this case the authors propose a distributed adaptive control scheme and prove that the proposed scheme guarantees that the tracking errors are bounded and small in the mean square sense provided the weakened interconnections and time delays are small enough. Finally, the authors present an illustrative example to present the applicability and effectiveness of the proposed schemes.

Application of adaptive filter in time delay estimation——generalized quadratic interpolation method

The time delay estimation (TDE) of two different received signals from the same source has attracted many interests of researchers in the field of signal processing. A method described for precisely estimating time delay in this paper is based on the assumption that little priori knowledge on statistical characteristics is available for the received signals. The variance of the estimate is derived . The basic architecture of this method is to use the adaptive noise canceller, in the steady state , and to interpolate the weight coefficients by using a generalized quadratic interpolation matrix. The formula of the time delay estimation is presented . The method proposed by F.A. Reed is a special case of this method . The hardware implementation is much easier than that of the conventional time delay estimation method . The results of the system simulation and the experimental results at sea show a good agreement with the theoretical analysis.

Design and Tool Flow of a Reconfigurable Asynchronous Neural Network Accelerator

Convolutional Neural Networks(CNNs)are widely used in computer vision,natural language processing,and so on,which generally require low power and high efficiency in real applications.Thus,energy efficiency has become a critical indicator of CNN accelerators.Considering that asynchronous circuits have the advantages of low power consumption,high speed,and no clock distribution problems,we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor(CMOS)process.Given the absence of a commercial design tool flow for asynchronous circuits,we develop a novel design flow to implement Click-based asynchronous bundled data circuits efficiently to mask layout with conventional Electronic Design Automation(EDA)tools.We also introduce an adaptive delay matching method and perform accurate static timing analysis for the circuits to ensure correct timing.The accelerator for handwriting recognition network(LeNet-5 model)is implemented.Silicon test results show that the asynchronous accelerator has 30%less power in computing array than the synchronous one and that the energy efficiency of the asynchronous accelerator achieves 1.538 TOPS/W,which is 12%higher than that of the synchronous chip.