Enumerative coding is an attractive algorithmic procedure for translating long source words into codewords and vice versa. The usage of long codewords makes it possible to approach a code rate which is as close as desired to Shannon’s noiseless capacity of the constrained channel. Enumerative encoding is prone to massive error propagation as a single bit error could ruin entire decoded words. T...

The RK5GL3 method is a numerical method for solving initial value problems in ordinary differential equations, and is based on a combination of a fifth-order Runge-Kutta method and 3-point Gauss-Legendre quadrature. In this paper we describe the propagation of local errors in this method, and show that the global order of RK5GL3 is expected to be six, one better than the underlying RungeKutta m...

Acknowledgements The work described in this thesis, and its description itself, spans over nearly a decade. During this time many people accompanied me and my work: supervisors and colleagues, friends and relatives, acquaintances and strangers have left their impact, be it stimulating or restricting, inspiring or correcting, aiding or abetting, encouraging or forbearing, loving or caring. Every...

The numerical error associated with finite-difference simulation of wave propagation in discontinuous media consists of two components. The first component is a higher order error that leads to grid dispersion; it can be controlled by higher-order methods. The second component results from misalignment between numerical grids and material interfaces. We provide an explicit estimate of the inter...

We describe and analyze the surprising evolution of an overflow error which has occurred during the simulation of a class of continuous complex systems called ‘fuzzy cellular automata’. This error not only perturbs the global behavior of the system but it generates its own interesting dynamics; in fact, it propagates over the original evolution as a binary cellular automaton in a structured, fr...

In this paper, we introduce a new Hough Transforni aimed at improving curve detection accuracy and robustness as well as coniputational eficiency. Robustness and accuracy improvement is achieved by analytically propagating the errors with image pixels to the estimated curve parameters. The errors with the curve parameters are then used to determine t k contribution of pixels to the accuniulator...

Neural networks have advantages of the high tolerance to noisy data as well as the ability to classify patterns having not been trained. While being applied in data mining, the time required to induce models from large data sets are one of the most important considerations. In this paper, we introduce a query-based learning scheme to improve neural networks' performance in data mining. Results ...

The related fields of mobile robotics and ground vehicle localization lack a linearized theory of odometry error propagation. By contrast, the equivalent Schuler dynamics which apply to inertial guidance have been known and exploited for decades. In this paper, the general solution of linearized propagation dynamics of both systematic and random errors for vehicle odometry is developed and vali...

We outline in this paper a hybrid method to propagate uncertainty in systems described by trees. Given a system described by a tree where nodes are basic operations and leafs are random variables described by their probability density functions (PDFs), one show that by a combination of exact computations with sampled versions of PDFs one can obtain the PDFs of output variables with great effici...

Abstra ct. A global gai n term is int rod uced into recurr ent a na log network s. T his gain ter m may he va ried as a. recurrent netwo rk se t-tles, similar to the way temperatu re is varied when "a nnealing" a networ k of stoc hast ic binary unit s. An err or propag ation algor it hm is presented which simultaneou sly opt imizes the weights and the gain schedule for a. recurrent network. Th ...