) which simply linearises all nonlinear models so that the traditional linear Kalman filter can be applied. Although the EKF (in its many forms) is a widely used filtering strategy, over thirty years of experience with it has led to a general consensus within the tracking and control community

The Time-Frequency and Time-Scale communities have recently developed a large number of overcomplete waveform dictionaries -- stationary wavelets, wavelet packets, cosine packets, chirplets, and warplets, to name a few. Decomposition into overcomplete systems is not unique, and several methods

This paper estimates the equivalence scale revealed by discretionary community allocations of welfare benefits to poor households. I apply the proposed approach to a subsidized rice program in Indonesia in which villages designated program beneficiaries, and estimate the equivalence scale implicit

employed; it does not imply a particular constitutive relation. The relevant equations for modeling the full complexity of the ocean include, as here, active tracers such as temperature and salt.) It builds on ideas developed in the computational fluid community. The numerical challenge is to ensure

equivalently, at most one congestion event every 1 2/3 hours). This is widely acknowledged as an unrealistic constraint. To address this limitation of TCP, this document proposes HighSpeed TCP, and solicits experimentation and feedback from the wider community.

. For both groups of older adults, simultaneous performance of an additional task increased the time taken to com-plete the TUG, with the greatest effect in the older adults with a history of falls. The TUG scores with or without an additional task (cognitive or manual) were equivalent with respect

. This impact is as large as an equivalent increase in non-farming assets or tripling the level of education. The data from the two surveys also allow the identification of some of the proximate channels through which social capital affects incomes: better publicly provided services, greater use of modern

Adiabatic quantum computation has recently attracted attention in the physics and computer science communities, but its computational power was unknown. We describe an efficient adiabatic simulation of any given quantum algorithm, which implies that the adiabatic computation model

according to the factorization X = RR T . The rank of the factorization, i.e., the number of columns of R, is chosen minimally so as to enhance computational speed while maintaining equivalence with the SDP. Fundamental results concerning the convergence of the algorithm are derived, and encouraging

A common misperception within the Neural Network community is that even with nonlinearities in their hidden layer, autoassociators trained with Backpropagation are equivalent to linear methods such as Principal Component Analysis (PCA). The purpose of this paper is to demonstrate that nonlinear