16283263
Robust classification of blurred imagery
In this paper, we present two novel approaches for the classification of blurry images. It is assumed that the blur is linear and space invariant, but that the exact blurring function is unknown. The proposed fusion-based approaches attempt to perform the simultaneous tasks of blind image restoration and classification. We call such a problem blind image fusion. The techniques are implemented using the nonnegativity and support constraints recursive inverse filtering (NAS-RIF) algorithm for blind image restoration and the Markov random field (RIRF)-based fusion method for classification by Schistad-Solberg et al. Simulation results on synthetic and real photographic data demonstrate the potential of the approaches. The algorithms are compared with one another and to situations in which blind blur removal is not attempted.
38019992
A comparative study of different chaos based spread spectrum communication systems
Using different properties of chaotic systems, different chaos based communication schemes have been proposed in the literature. However, their performances are seldom compared. In this paper, we implement several major chaos based communication methods including chaotic spreading codes, chaotic carrier, chaos shift keying, chaotic masking and chaotic parameter modulation in a common digital communication background. Their performance in terms of bit error rate and robustness are then evaluated.
11779035
Chaotic binary sequences for efficient wireless multipath channel estimation
This paper presents a better binary sequence design for efficient wireless multipath channel estimation. Chaotic binary sequences with better properties than conventional maximal length sequences are obtained through an optimization algorithm based on DNA computation. The proposed method is attractive due to its ability to generate binary sequences for specific design criteria. The generated chaotic binary sequences have superior performance compared to maximal length sequences and have complexity similar to the levels of shift register implementation. The effectiveness of the proposed method was evaluated for sequence design for frequency domain channel estimation. Simulation results clearly show the improved performance of the sequence obtained using the proposed scheme over the maximal length sequence. Further, the proposed scheme is not only limited to channel estimation sequence design but can be applied to various communication system design problems.
18767073
Fitting Ellipses to a Region with Application in Calligraphic Stroke Reconstruction
Given a region, it is a challenge to find a set of primitive shapes such as rectangles, circles or ellipses to cover it. This is in fact a set-covering problem, which is known to be NP-hard. The focus of this paper is on fitting a set of ellipses onto an image region. This problem was first formulated by identifying a number of criteria required for the ellipse fitting. A solution is then proposed for automatically determining the set of ellipses that best fits onto an image region. The proposed ellipse fitting algorithm has also been applied to strokes forming characters of Chinese calligraphic artwork. The results show that our proposed algorithm generates ellipses fitting onto stroke regions and capturing the characteristics of the strokes during turning, tilting and back-trace.
33950301
Measuring Nondeterminism in Pushdown Automata
The amount of nondeterminism that a pushdown automaton requires to recognize an input string can be measured by the minimum number of guesses that it must make to accept the string, where guesses are measured in bits of information. When this quantity is unbounded, the rate at which it grows as the length of the string increases serves as a measure of the pushdown automaton's “rate of consumption” of non-determinism. We show that this measure is similar to other complexity measures in that it gives rise to an infinite hierarchy of complexity classes of context-free languages differing in the amount of this resource (nondeterminism) that they require. In addition, we show that there are contextfree languages that can only be recognized by a pushdown automaton whose nondeterminism grows linearly, resolving an open problem in the literature. In particular, {ww R : we {a,b}}*} is such a language.
18854339
Brush Writing Style Classification from Individual Chinese Characters
Chinese calligraphic artwork usually contains a few or even a single character. In order to perform automatic brush writing style classification on these kinds of Chinese calligraphic images, existing approaches need to be modified because they assume that many characters of the same style exist in the input image. A novel approach is proposed to address the brush writing style classification problem for single-character Chinese calligraphic images by combining the texture analysis and the structural information through a set of parameterised ellipses
17124839
Separating Exponentially Ambiguous Finite Automata from Polynomially Ambiguous Finite Automata
We resolve an open problem raised by Ravikumar and Ibarra [SIAM J. Comput., 18 (1989), pp. 1263--1282] on the succinctness of representations relating to the types of ambiguity of finite automata. We show that there exists a family of nondeterministic finite automata {An} over a two-letter alphabet such that, for any positive integer n, An is exponentially ambiguous and has n states, whereas the smallest equivalent deterministic finite automaton has 2n states, and any smallest equivalent polynomially ambiguous finite automaton has 2n -1 states.
42246755
A Constraint-Based Interactive Train Rescheduling Tool
In this paper, we formulate train rescheduling as constraint satisfaction problem and describe a constraint propagation approach to tackle it. Algorithms for timetable verifications and train rescheduling are designed under a coherent framework. We define two optimality criteria that correspond to minimizing passenger delay and the number of station visit modifications respectively for rescheduling. Two heuristics are then proposed to speed up and direct the search towards the optimal solutions. The feasibility of our proposed algorithms and heuristics are confirmed with experimentation using real-life data.