Designing Leakage-Tolerant and Noise-Immune Enhanced Low Power Wide OR Dominos in Sub-70nm CMOS Technologies

Two new circuit techniques to suppress leakage currents and enhance noise immunity while decreasing the active power are proposed. Eight-input OR gate circuits constructed with these techniques are simulated using 45nm BSIM4 SPICE models in HSPICE. The simulation results show that the proposed circuits effectively lower the active power, reduce the total leakage current, and enhance speed under similar noise immunity conditions. The active power of the two proposed circuits can be reduced by up to 8. 8% and 11.8% while enhancing the speed by 9.5% and 13.7% as compared to dual Vt domino OR gates with no gating stage. At the same time,the total leakage currents are also reduced by up to 80.8% and 82.4% ,respectively. Based on the simulation results,the state of the evaluation node is also discussed to reduce the total leakage currents of dual Vt dominos.

Stochastic responses of tumor-immune system with periodic treatment

We investigate the stochastic responses of a tumor–immune system competition model with environmental noise and periodic treatment. Firstly, a mathematical model describing the interaction between tumor cells and immune system under external fluctuations and periodic treatment is established based on the stochastic differential equation. Then, sufficient conditions for extinction and persistence of the tumor cells are derived by constructing Lyapunov functions and Ito＇s formula. Finally, numerical simulations are introduced to illustrate and verify the results. The results of this work provide the theoretical basis for designing more effective and precise therapeutic strategies to eliminate cancer cells, especially for combining the immunotherapy and the traditional tools.

Bearing Fault Diagnosis Method of Wind Turbine Based on Improved Anti-Noise Residual Shrinkage Network

Aiming at the difficulty of rolling bearing fault diagnosis of wind turbine under noise environment,a new bearing fault identification method based on the Improved Anti-noise Residual Shrinkage Network(IADRSN)is proposed.Firstly,the vibration signals of wind turbine rolling bearings were preprocessed to obtain data samples divided into training and test sets.Then,a bearing fault diagnosis model based on the improved anti-noise residual shrinkage network was established.To improve the ability of fault feature extraction of the model,the convolution layer in the deep residual shrinkage network was replaced with a Dense-Net layer.To further improve the anti-noise ability of the model,the first layer of the model was set as the Drop-block layer.Finally,the labeled data samples were used for training model and the trained model was applied to the test set to output the fault diagnosis results.The results showed that the proposed method could achieve the fault diagnosis of wind turbine bearing more accurately in the high noise environment through comparison and verification.

High-Speed,Robust CMOS Dynamic Circuit Design

A novel circuit with a narrow pulse driving structure is proposed for enhancing the noise immunity and improving the performance of wide fan-in dynamic circuits. Also,an analytical mode that agrees well with simulations is presented for transistor sizing. Simulation results show that an improvement of up to 12% over the conventional technique at 1GHz is obtained with this circuit,which can run 1.6 times faster than the existing technique with the same noise immunity.

Classification of Images Based on a System of Hierarchical Features

The results of the development of the new fast-speed method of classification images using a structural approach are presented.The method is based on the system of hierarchical features,based on the bitwise data distribution for the set of descriptors of image description.The article also proposes the use of the spatial data processing apparatus,which simplifies and accelerates the classification process.Experiments have shown that the time of calculation of the relevance for two descriptions according to their distributions is about 1000 times less than for the traditional voting procedure,for which the sets of descriptors are compared.The introduction of the system of hierarchical features allows to further reduce the calculation time by 2–3 times while ensuring high efficiency of classification.The noise immunity of the method to additive noise has been experimentally studied.According to the results of the research,the marginal degree of the hierarchy of features for reliable classification with the standard deviation of noise less than 30 is the 8-bit distribution.Computing costs increase proportionally with decreasing bit distribution.The method can be used for application tasks where object identification time is critical.

Estimation of plasma equilibrium parameters via a neural network approach

Plasma equilibrium parameters such as position, X-point, internal inductance, and poloidal beta are essential information for efficient and safe operation of tokamak. In this work, the artificial neural network is used to establish a non-linear relationship between the measured diagnostic signals and selected equilibrium parameters. The estimation process is split into a preliminary classification of the kind of equilibrium(limiter or divertor) and subsequent inference of the equilibrium parameters. The training and testing datasets are generated by the tokamak simulation code(TSC), which has been benchmarked with the EAST experimental data. The noise immunity of the inference model is tested. Adding noise to model inputs during training process is proved to have a certain ability for maintaining performance.

Detection Scheme of Positive Sequence Components Based on Operation Period Delay Filter

Fast and accurate acquisition of positive sequence components of unbalanced grid voltage is an essential requirement to ensure the safety operation of the grid-connected inverter.To improve the extraction speed of positive sequence components of unbalanced voltage,this study proposes a sampling period delay filter(SPDF)to quickly separate positive and negative sequence components by delaying two sampling periods of grid voltage in dq frame.With the SPDF method,only one coordinate transformation is required and the computational burden can be reduced apparently.Then,the noise immunity performance of the proposed SPDF algorithm is investigated;and the corresponding solution,operation period delay filter(OPDF),can guarantee the desired fast response performance under the premise of limiting the amplified noise within the acceptable range.Finally,the feasibility and priority of the above two algorithms have been verified by the simulation and experimental results.

Analysis of Staggered OFDM Data Transmission With Reduced Complexity

The complexity and performance of staggered orthogonal frequency division multiplexed (OFDM)data transmission systems are discussed in this paper. As improved digital implemention with a computationalcomplexity reduction of 30% compared to previous systems￣[7] is Presented. Staggered OFDM data transmission canprovide high bandwidth efficiency vecy close to 2log_2M for M-ary signalling. For voiceband channels, improve-ment of 3dB and 12dB in Gaussian noise and impulse noise immunities respectively, are abtained over serial QAMtransmission. An analysis of the phase jitter immunsity for the staggered OFDM system with raised cosine shapingfilters is presented. The analysis and simulation results show that a staggered delay of half a baud period betweensubchannels with a 100% rolloff factor optimize the system performance phase jitter and provide an improve-ment of 2dB in phase jitter immunity over nonstaggered systems.