This paper proposes a new adaptive extended Kalman filter (AEKF) for a class of nonlinear systems perturbed by noise which is not necessarily additive. The proposed filter is adaptive against the uncertainty in the process and measurement noise covariances. This is accomplished by deriving two recursive updating rules for the noise covariances, these rules are easy to implement and reduce the n...

We investigate the idea that linear contracts are reliable because they give the same incentives for effort at every point along the contract. We ask whether this reliability leads to a microfoundation for linear contracts, when the principal is profit-maximizing. We consider a principal-agent model with risk neutrality and limited liability, in which the agent observes the realization of a mea...

We review the capacity-achieving coding scheme for the power-constrained wide-band Additive White Gaussian Noise (AWGN) channel (with noiseless feedback) that was proposed in [1]. The performance of this scheme for the cases of (i) non-Gaussian additive white noise on the forward path, and (ii) AWGN on both forward and feedback paths, is also discussed.

From the early days in his career, Sid Yakowitz showed interest in noisy function optimization. He realized the universality of random search as an optimization paradigm, and was particularly interested in the minimization of functions Q without making assumptions on the form of Q. Especially the noisy optimization problem appealed to him, as exact computations of Q come often at a tremendous c...

Hadamard multiplexing provides a considerable SNR boost over additive random noise but Poisson noise such as photon noise reduces the boost. We develop the theory for full H-matrix Hadamard transform imaging under additive and Poisson noise effects. We show that H-matrix encoding results in no effect on average on the noise level due to Poisson noise sources while preferentially reducing additi...

This research studied the effect of additive and multiplicative noise in images, and their solution. Salt n pepper, and Gaussian noise is considered as a additive noise, while impulsive noise is considered as a multiplicative noise. For additive noise, this paper presents the outcome of Wiener filter, and Pseudo inverse filter, while for impulsive noise, we studied wavelet denoising. A hybrid f...

Noise enhanced hypothesis-testing is studied according to the restricted Neyman-Pearson (NP) criterion. First, a problem formulation is presented for obtaining the optimal probability distribution of additive noise in the restricted NP framework. Then, sufficient conditions for improvability and nonimprovability are derived in order to specify if additive noise can or cannot improve detection p...

We formulate linear dimensionality reduction as a semi-parametric estimation problem, enabling us to study its asymptotic behavior. We generalize the problem beyond additive Gaussian noise to (unknown) nonGaussian additive noise, and to unbiased non-additive models.