6994949
Ergodic chaotic parameter modulation with application to digital image watermarking
This paper presents a novel technique for image watermarking based on chaos theory. Chaotic parameter modulation (CPM) is employed to modulate the copyright information into the bifurcating parameter of a chaotic system. The system output is a wideband signal and is used as a watermark to be inserted into the host image. In the detection, a novel method based on the ergodic property of chaotic signal is developed to demodulate the embedded copyright information. Compared to previous works on blind watermarking, the proposed technique can effectively remove the interference from the host image and, thus, improve the detection performance dramatically. Simulation results show that the ergodic CPM approach is effective for image watermarking in terms of noise performance, robustness against attacks, and payload. In addition, its implementation is very simple and the computation speed is fast. Compared to holographic transform domain method and the conventional spread spectrum watermarking scheme, the proposed technique is shown to be superior.
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.
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.
33568725
A novel M-ary chaotic spread spectrum communication scheme for DSRC system in ITS
In this paper, a novel non-coherent M-ary chaotic spread spectrum communication scheme is proposed for dedicated short range communications (DSRC) in intelligent transportation systems (ITS). The proposed scheme encodes the M-ary information symbols on to the bifurcation parameter of a chaotic system. This new chaotic communication scheme exploits the ergodic properties of chaotic signals for demodulating the received signal. The proposed scheme is basically non-coherent which eliminates the complex synchronization procedure. Furthermore, the proposed scheme utilizes a low complexity multipath mitigation technique to combat fading. Performance analysis shows the superior communication performance of the proposed chaotic spread spectrum scheme over conventional spread spectrum schemes in rapid multipath fading environments. Thus, the developed scheme is attractive in terms of communication performance, multipath mitigation, and system complexity.
8282971
Protein Subcellular Localization Based on Psi-blast and Machine Learning
Subcellular location is an important functional annotation of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is necessary for large-scale genome analysis. This paper describes a protein subcellular localization method which extracts features from protein profiles rather than from amino acid sequences. The protein profile represents a protein family, discards part of the sequence information that is not conserved throughout the family and therefore is more sensitive than the amino acid sequence. The amino acid compositions of whole profile and the N-terminus of the profile are extracted, respectively, to train and test the probabilistic neural network classifiers. On two benchmark datasets, the overall accuracies of the proposed method reach 89.1% and 68.9%, respectively. The prediction results show that the proposed method perform better than those methods based on amino acid sequences. The prediction results of the proposed method are also compared with Subloc on two redundance-reduced datasets.
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.
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.
206606389
e-Learning Martial Arts
Traditionally, when people want to learn martial arts, they have to go to training clubs and learn under the coach together with the other students. To reduce the tuition fees, there are usually a lot of students under a single coach and hence, it is difficult for the students to get enough suggestions in the class. It would be far easier if the students could practice themselves at home and ask for suggestions from a virtual coach in the computer. Occasionally, in case they find difficulties going to the next step, they may then approach the real coach for suggestions and training. In this paper, we propose such a training system based on the motion capture system. The system automatically analyzes the motions of the player and gives suggestions. The students can also view the martial art techniques stored in the system or their own techniques captured by the motion capture system from various points of view in order to gain objective ideas of the techniques.
32788724
Tight Lower Bounds on the Size of Sweeping Automata
A sweeping automaton is a two-way deterministic finite automaton which makes turns only at the endmarkers. We say that a sweeping automaton is degenerate if the automaton has no left-moving transitions. We show that for each positive integer n, there is a nondeterministic finite automaton An over a two-letter alphabet such that An has n states, whereas the smallest equivalent nondegenerate sweeping automaton has 2n states.