Some new results about estimation of attraction domain of memory patterns and exponential convergence rate of the network trajectories to memory patterns for Hopfield continuous associative memory are obtained by using of some new technics and Lyapunov method.
In this paper, by constructing Liapunov functional and some analysis techniques, we study the periodic solutions of a neural network as follows: dxdt=-x(t)-α tanh+I1(t) dydt=-y(t)-α tanh+I2(t) and obtain some sufficient conditions to ensure the network exist a unique periodic solution, and its all solutions converge exponentially to the periodic solution.
It is concerned with L 1-control of continuous affine nonlinear systems with prescribed exponentially convergent rate and performance by using set-valued analysis method.
In those conditions all solutions of the proposed neural network were globally exponentially convergent to the unique solution to the linear variational inequality problem, and the estimation of the exponential convergence rates of the neural network was obtained.
For the stabilization control law design using on the dynamic positioning and position mooring of underactuated surface vessels, based on the method of σ -process, a convergence control item is added in the original equations to control the converge rate of the whole system. A smooth time-varying feedback stabilization law with exponentially convergence rate is obtained. The aim of stabilization control of underactuated surface vessels is achieved.
The exponential convergence rate in entroy is studied for symmetric forms, with a special attention to the Markov chain with a state space having two points only.
The exponential convergence of the adaptive projection algorithm in finite-dimensional Hilbert spaces is constructively proved, with exponential decay ratios given with high accuracy.
The attraction domains of memory patterns and exponential convergence rate of the network trajectories to memory patterns for continuous feedback associative memory are estimated.
Moreover, for the exponentially stable system, the exponential convergence rates of the system's states can be estimated by some parameters of the LMIs.
We establish that if the noise is at the same time sufficiently smooth and non-degenerate in space, then the weak solutions converge exponentially fast to equilibrium.
By employing Halanay inequalities, we obtain delay independent sufficient conditions for the networks to converge exponentially toward encoded patterns associated with the external stimuli.
This problem is solved by inverting the Laplace transform with respect to time on a contour in the complex plane using an exponentially convergent quadrature rule.
Each diagram evaluates to 10 000 digits in seconds, because the primitive words are transformable to exponentially convergent single sums, as recently shown for and , familiar in QCD.
This empirical relation has been checked at 1,000-digit precision and readily yields 50,000 digits of , after transformation to an exponentially convergent sum, akin to those studied in math.CA/9803067.
This paper provides a scheme for robust pole placement. The scheme is applicable to general plants which are discribed by single variable discrete time linear equations and are both controllable and observable, provided that the order of the plant or both the order of the plant and the time of delay are known.The adaptive control mechanism designed on pole placement consists of a parameter estimator, a controller (seen as a combination of a state observer and a generator of state feedback) and an external p...
A new identification algorithm given in this paper is applicable to deterministic adaptive control systems. A peculiar advantage of this algorithm is that the expoien-tial convergence of the parameter estimates can be guaranteed if the regression vectors are made well exciting during some time interval of finite length.
The decentralized adaptive control of a class of large scale systems is investigated in this paper. A group of adaptive laws with stronger robustness are given. When there exists among vatious subsystems an arbitrary interconnection with unknown parameters, nonlinearities and bound disturbances, the state and parameter errors will converge to the bound residual sets exponenetially if the relative degree n~* of the transfer function of each decoupled subsystem is less than or equal to two.