This paper concerns the memoryless quasi-Newton method, that is precisely the quasi-Newton method for which the approximation to the inverse of Hessian, at each step, is updated from the identity matrix. Hence its search direction can be computed without the storage of matrices. In this paper, a scaled memoryless symmetric rank one (SR1) method for solving large-scale unconstrained optimization...

<p style='text-indent:20px;'>Memoryless quasi–Newton updating formulas of BFGS (Broyden–Fletcher–Goldfarb–Shanno) and DFP (Davidon–Fletcher–Powell) are scaled using well-structured diagonal matrices. In the scaling approach, elements as well eigenvalues memoryless play significant roles. Convergence analysis given diagonally methods is discussed. At last, performance numerically tested on...

steganography, watermarking, information hiding, error exponent, random coding Watermarking codes are analyzed from an informationtheoretic viewpoint as a game between an information hider and an active attacker. While the information hider embeds a secret message (watermark) in a covertext message (typically, text, image, sound, or video stream) within a certain distortion level, the attacker ...

Derived from the idea of stochastic approximation, recursive algorithms to identify a Hammerstein system are presented. Two of them recover the characteristic of the nonlinear memoryless subsystem while the third one estimates the impulse response of the linear dynamic part. The a priori information about both subsystems is nonparametric. Consistency in quadratic mean is shown and the convergen...

Multi-Input Single-Output (MISO) Wiener system is comprised of a multidimensional linear subsystem and a memoryless nonlinear block. In this paper a disturbed MISO Wiener system is concerned, of which the nonlinearity is discontinuous piece-wise linear characteristic. A recursive algorithm is proposed for identifying all of unknown system parameters. It is shown that the algorithm is convergent...