Entropy is a fundamental property of a repertoire. Here, we present an efficient algorithm to estimate the entropy of types with the help of Zhang’s estimator. The algorithm takes advantage of the fact that the number of different frequencies in a text is in general much smaller than the number of types. We justify the convenience of the algorithm by means of an analysis of the statistical prop...

If a quantum computer is stabilized by fault-tolerant quantum error correction (QEC), then most of its resources (qubits and operations) are dedicated to the extraction of error information. Analysis of this process leads to a set of central requirements for candidate computing devices, in addition to the basic ones of stable qubits and controllable gates and measurements. The logical structure...

The problem of coding low-entropy information sources is considered. Since the run-length code was offered about 50 years ago by Shannon, it is known that for such sources there exist coding methods much simpler than for sources of a general type. However, known coding methods of low-entropy sources do not reach the given redundancy. In this correspondence, a new method of coding low-entropy so...

We present the rst known case of one-dimensional and two-dimensional string matching algorithms for text with bounded entropy. Let n be the length of the text and m be the length of the pattern. We show that the expected complexity of the algorithms is related to the entropy of the text for various assumptions of the distribution of the pattern. For the case of uniformly distributed patterns, o...

Differential entropy is a quantity used in many signal processing problems. Often we need to calculate not only the entropy itself, but also its gradient with respect to various variables, for efficient optimization, sensitivity analysis, etc. Entropy estimation can be based on an estimate of the probability density function, which is computationally costly if done naively. Some prior algorithm...

Fermi acceleration is the process of energy transfer from massive objects in slow motion to light objects that move fast. The model for such process is a time-dependent Hamiltonian system. As the parameters of the system change with time, the energy is no longer conserved, which makes the acceleration possible. One of the main problems is how to generate a sustained and robust energy growth. We...

This paper describes the implementation of a multidimensional block-matching nonrigid registration algorithm. The main features of the algorithm are its simplicity, its free form nature, the modularity of the similarity measure, which makes it possible using local entropy-based similarity measures and the avoidance of the optimization module. The algorithm implementation described in this paper...

Multithreshold Entropy Linear Classifier (MELC) is a density based model which searches for a linear projection maximizing the CauchySchwarz Divergence of dataset kernel density estimation. Despite its good empirical results, one of its drawbacks is the optimization speed. In this paper we analyze how one can speed it up through solving an approximate problem. We analyze two methods, both simil...

Maximum entropy models are considered by many to be one of the most promising avenues of language modeling research. Unfortunately, long training times make maximum entropy research difficult. We present a novel speedup technique: we change the form of the model to use classes. Our speedup works by creating two maximum entropy models, the first of which predicts the class of each word, and the ...

Automatic facial recognition has many potential applications in different areas of humancomputer interaction. However, they are not yet fully realized due to the lack of an effectivefacial feature descriptor. In this paper, we present a new appearance based feature descriptor,the local directional pattern (LDP), to represent facial geometry and analyze its performance inrecognition. An LDP feat...