(1963). Cybernetics, or Control and Communication in the Animal and the Machine. Technometrics: Vol. 5, No. 1, pp. 128-130.

Cybernetics, or Control and Communication in the Animal and the Machine

As a robust nonlinear similarity measure in kernel space, correntropy has received increasing attention in domains of machine learning and signal processing. In particular, the maximum correntropy criterion (MCC) has recently been successfully applied in robust regression and filtering. The default kernel function in correntropy is the Gaussian kernel, which is, of course, not always the best choice. In this paper, we propose a generalized correntropy that adopts the generalized Gaussian density (GGD) function as the kernel, and present some important properties. We further propose the generalized maximum correntropy criterion (GMCC) and apply it to adaptive filtering. An adaptive algorithm, called the GMCC algorithm, is derived, and the stability problem and steady-state performance are studied. We show that the proposed algorithm is very stable and can achieve zero probability of divergence (POD). Simulation results confirm the theoretical expectations and demonstrate the desirable performance of the new algorithm.

Generalized Correntropy for Robust Adaptive Filtering

Maximum correntropy Kalman filter

Effective connectivity: Influence, causality and biophysical modeling

The maximum correntropy criterion (MCC) has received increasing attention in signal processing and machine learning due to its robustness against outliers (or impulsive noises). Some gradient based adaptive filtering algorithms under MCC have been developed and available for practical use. The fixed-point algorithms under MCC are, however, seldom studied. In particular, too little attention has been paid to the convergence issue of the fixed-point MCC algorithms. In this letter, we will study this problem and give a sufficient condition to guarantee the convergence of a fixed-point MCC algorithm.

Convergence of a Fixed-Point Algorithm under Maximum Correntropy Criterion

From the viewpoint of information theory, we proposed a novel concept of information coupling (IC) between the variables of MIMO dynamic system. Two kinds of measures of information coupling strength (ICS) were formulated in terms of mutual information rates. We also derived the frequency formulae of information coupling strengths for MIMO LTI system. Connections between information decoupling and conventional dynamic decoupling of linear system were presented, i.e. the input-output information decoupling (IOID) is equivalent to the input-output dynamic decoupling (IODD), whereas the output information decoupling (OID) is just a necessity for IOID and IODD. Our work shall introduce a new approach for further study of decoupling control under the information-theoretic framework.

Measuring the Couplings of MIMO Dynamic Systems: An Information-Theoretic Approach

Minimum entropy control has been studied extensively. Controllers satisfying a closed-loop minimum entropy condition provide a means of trading off the robustness of Hinfin control with the performance of H2 controller. In this paper, the minimum entropy Hinfin mixed sensitivity method is described, followed by the controller design for an aircraft longitudinal flight control. Analysis tests and simulations illustrate that the minimum entropy controller has better performances than most of the other Hinfin controllers which belong to a certain subset of the "unit ball in Hinfin"

The Application of Minimum Entropy H Mixed Sensitivity to Flight Control

A coarse motion and fine motion integrated reticle stage driven by a planar motor comprises a movable platform ( 100 ) of the reticle stage, a balance mass ( 200 ), a drive motor, a mask plate ( 101, 102 ), a base ( 001 ), a vibration isolation system ( 500 ), and a measuring system, wherein, the vibration isolation system is located between the balance mass and the base, and the mask plate is mounted on the movable platform The drive motor of the movable platform is a moving-iron type planar motor ( 300 ) The reticle stage can lower the design complexity of the drive motor of the movable platform Compared with a linear motor, the planar motor can provide push forces in more directions, the number of motors is reduced, the structure of the movable platform is more compact, the inherent frequency and the control bandwidth of the movable platform are improved, and thus control precision is improved

Coarse motion and fine motion integrated reticle stage driven by planar motor

Parameter estimation is a key step in system identification. In the third chapter, we give a brief but comprehensive overview of information theoretic approaches for parameter estimation, such as the maximum entropy estimation, minimum divergence estimation, and minimum error entropy estimation, and discuss the connections between information theoretic methods and conventional alternatives. At the end of the chapter, we also give a brief overview of several well-known information criteria for model selection.

Information Theoretic Parameter Estimation

In this paper satisfactory control for discrete-time linear periodic systems is studied. Based on a suitable time-invariant state sampled reformulation, periodic state feedback controller has been designed such that desired requirements of steady state covariance, H-infinity rejection bound and regional pole assignment for the periodic system are met simultaneously. By using satisfactory control theory, the problem of satisfactory periodic controller can be transformed into a linear programming problem subject to a set of linear matrix inequalities (LMIs), and a feasible designing approach is presented via LMI technique. Numeric example validates the obtained conclusion.

Jinchun Hu

Papers

Measuring the Couplings of MIMO Dynamic Systems: An Information-Theoretic Approach

The Application of Minimum Entropy H Mixed Sensitivity to Flight Control

Coarse motion and fine motion integrated reticle stage driven by planar motor

Information Theoretic Parameter Estimation

Satisfactory control of discrete-time linear periodic systems