Hongzhou Tan

Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion

This technical note presents theoretical analysis and simulation results on the performance of a classic gradient neural network (GNN), which was designed originally for constant matrix inversion but is now exploited for time-varying matrix inversion. Compared to the constant matrix-inversion case, the gradient neural network inverting a time-varying matrix could only approximately approach its time-varying theoretical inverse, instead of converging exactly. In other words, the steady-state error between the GNN solution and the theoretical/exact inverse does not vanish to zero. In this technical note, the upper bound of such an error is estimated firstly. The global exponential convergence rate is then analyzed for such a Hopfield-type neural network when approaching the bound error. Computer-simulation results finally substantiate the performance analysis of this gradient neural network exploited to invert online time-varying matrices.

HOS-based nonparametric and parametric methodologies for machine fault detection

A framework for the detection and identification of machine faults through vibration measurements and higher order statistics (HOS) analysis is presented. As traditional signal processing techniques are based on the nonparametric magnitude analysis of vibration signals, in this paper, two different state-of-the-art HOS-based methods, namely, a nonparametric phase-analysis approach and a parametric linear or nonlinear modeling approach are used for machine fault diagnostic analysis. The focus of this paper is on the application of the techniques, not on the underlying theories. Each technique is described briefly and is accompanied by an experimental discussion on how it can be applied to classify the synthetic mechanical and electrical faults of induction machines compared with their normality. Promising results were obtained which show that the presented methodologies are possible approaches to perform effective preventive maintenance in rotating machinery.

MATLAB Simulink modeling and simulation of LVI-based primal-dual neural network for solving linear and quadratic programs

In view of parallel-processing nature and circuit-implementation convenience, recurrent neural networks are often employed to solve optimization problems. Recently, a primal-dual neural network based on linear variational inequalities (LVI) was developed by Zhang et al. for the online solution of linear-programming (LP) and quadratic-programming (QP) problems simultaneously subject to equality, inequality and bound constraints. For the final purpose of field programmable gate array (FPGA) and application-specific integrated circuit (ASIC) realization, we investigate in this paper the MATLAB Simulink modeling and simulative verification of such an LVI-based primal-dual neural network (LVI-PDNN). By using click-and-drag mouse operations in MATLAB Simulink environment, we could quickly model and simulate complicated dynamic systems. Modeling and simulative results substantiate the theoretical analysis and efficacy of the LVI-PDNN for solving online the linear and quadratic programs.

Repetitive Learning Control of Nonlinear Continuous-Time Systems Using Quasi-Sliding Mode

In this brief, a quasi-sliding mode (QSM)-based repetitive learning control (RLC) method is proposed for tackling multi-input multi-output nonlinear continuous-time systems with matching perturbations. The proposed RLC method is able to perform rejection of periodic exogenous disturbances as well as tracking of periodic reference trajectories. It ensures a robust system stability when it is subject to nonperiodic uncertainties and disturbances. In this brief, an application to a robotic manipulator is used to illustrate the performance of the proposed QSM-based RLC method. A comparative study with the conventional variable structure control (VSC) technique is also included

Semiblind identification of nonminimum-phase ARMA models via order recursion with higher order cumulants

This paper develops a novel identification methodology for nonminimum-phase autoregressive moving average (ARMA) models of which the models orders are not given. It is based on the third-order statistics of the given noisy output observations and assumed input random sequences. The semiblind identification approach is thereby named. By the order-recursive technique, the model orders and parameters can be determined simultaneously by minimizing well-defined cost functions. At each updated order, the AR and MA parameters are estimated without computing the residual time series (RTS), with the result of decreasing the computational complexity and memory consumption. Effects of the AR estimation error on the MA parameters estimation are also reduced. Theoretical statements and simulations results, together with practical application to the train vibration signals modeling, illustrate that the method provides accurate estimates of unknown linear models, despite the output measurements being corrupted by arbitrary Gaussian noises of unknown pdf.

The Half-Width Microstrip Leaky Wave Antenna With the Periodic Short Circuits

A half-width microstrip leaky wave antenna (LWA) with periodic short circuits is presented. The backward-to-forward beam-scanning capability is achieved by periodic construction. The proposed antenna consists of a long rectangular patch with the short circuits that are placed with a series of shorting pins between the antenna patch and the ground plane periodically. The measurement results show that the main lobe scans electronically from 144° to 41° in H-plane (y-z plane) toward endfire (+z direction) with an open stopband when the operating frequency is increased from 4.4 GHz to 8.8 GHz.

A Highly Stable and Reliable 13.56-MHz RFID Tag IC for Contactless Payment

Radio frequency identification (RFID) has been widely used for contactless payment. However, modifying sensitive data such as balance stored in an RFID tag over an air interface requires high stability and reliability, particularly when the tag is being moved away from the RFID reader (such phenomenon is called card tear). Previous countermeasures of card tear operation are mainly based on contact smart card; however, when the tag is contactless, the variation of magnetic field should be also taken into account. To solve card tear problem, this paper presents a fully integrated 13.56-MHz RFID tag IC with reliable power supply and antitearing mechanism. Proposed are the following solutions: 1) to provide a 4-kV multifunction electrostatic discharge protection circuit with rectifier and limiter; 2) to develop a low dropout circuit and a low voltage detection circuit; 3) to design a well-run antitearing mechanism, which can protect the tag from being incorrectly written; and 4) to design a digital circuit with several functions, including 3DES, micro control unit, and electrically erasable programmable read-only memory. The proposed RFID tag IC was fabricated using a 0.18-μm process with an area of 3 mm2. The measured results indicate that the tag operates in a stable and reliable mode without any problem caused by card tear.

Novel Dual-Frequency Microstrip Antenna With Narrow Half-Ring and Half-Circular Patch

A novel dual-frequency microstrip antenna is presented. The dual-frequency is generated through a half-ring structure and a half-circular patch element. The half-ring is narrower than the conventional ring antenna, and the parameters that decide the resonant frequency of the antenna are studied. Simulation and measurement results show that the proposed antenna works at 0.9 and 1.8 GHz.

A Dual Frequency Microstrip Antenna Using a Double Sided Parallel Strip Line Periodic Structure

A dual-frequency microstrip antenna is presented. The proposed antenna consists of a rectangular radiating patch, the ground, and a periodic offset double-sided parallel-strip line structure that is used as the substrate. The phase constant of the substrate is less than 0 at the frequency of operation, which makes the rectangular microstrip antenna work in different modes, and has two resonant frequencies. Experimental results show that the proposed antenna works at 3.3 GHz and 3.9 GHz.

A Compact Fractal Loop Rectenna for RF Energy Harvesting

This letter presents a compact fractal loop rectenna for RF energy harvesting at GSM1800 bands. First, a fractal loop antenna with novel in-loop ground-plane impedance matching is proposed for the rectenna design. Also, a high-efficiency rectifier is designed in the loop antenna to form a compact rectenna. Measured results show that an efficiency of 61% and an output dc voltage of 1.8xa0V have been achieved over 12-kΩ resistor for 10xa0μW/cm2 power density at 1.8xa0GHz. The rectenna is able to power up a battery-less LCD watch at a distance of 10xa0m from the cell tower. The proposed rectenna is compact, easy to fabricate, and useful for various energy harvesting applications.