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.
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.
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.
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.
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
15674805
Animating reactive motions for biped locomotion
In this paper, we propose a new method for simulating reactive motions for running or walking human figures. The goal is to generate realistic animations of how humans compensate for large external forces and maintain balance while running or walking. We simulate the reactive motions of adjusting the body configuration and altering footfall locations in response to sudden external disturbance forces on the body. With our proposed method, the user first imports captured motion data of a run or walk cycle to use as the primary motion. While executing the primary motion, an external force is applied to the body. The system automatically calculates a reactive motion for the center of mass and angular momentum around the center of mass using an enhanced version of the linear inverted pendulum model. Finally, the trajectories of the generalized coordinates that realize the precalculated trajectories of the center of mass, zero moment point, and angular momentum are obtained using constrained inverse kinematics. The advantage of our method is that it is possible to calculate reactive motions for bipeds that preserve dynamic balance during locomotion, which was difficult using previous techniques. We demonstrate our results on an application that allows a user to interactively apply external perturbations to a running or walking virtual human model. We expect this technique to be useful for human animations in interactive 3D systems such as games, virtual reality, and potentially even the control of actual biped robots.
14116300
A New Perspective of the Proportional Sampling Strategy
To compare the performance of different testing strategies, P-measure and E-measure are two effectiveness measures used in previous analytical studies. P-measure, which is defined as the probability of detecting at least one failure, is a measure of how likely it is that failure-causing inputs are selected at least once as test cases. E-measure, which is defined as the expected number of failures detected, is a measure of how frequently failure-causing inputs are selected as test cases. However, we have noa priori knowledge of how many failure-causing inputs there are, or where they may lie. In this paper, we study P-measure and E-measure in terms of how much attention an arbitrary input receives. In the context of P-measure, the attention received by an arbitrary input is the probability that the input is selected at least once as a test case, while in the context of E-measure, the attention is the expected number of times that an input is selected as a test case. The attentions received by an input using the proportional sampling strategy and random testing are then compared. The attention received by an input is found to be the same under the two testing strategies for E-measure, whereas for P-measure the attention is always higher for the proportional sampling strategy than for random testing. This new perspective allows us to provide simpler proofs of some known results. Furthermore, we are able to show that the difference in the expected number of distinct test cases considered by the proportional sampling strategy is larger than that of random testing by at most 2k, wherek is the number of partitions and is independent of the number of test cases selected.
35321520
Reconstructing the Correct Writing Sequence from a Set of Chinese Character Strokes
A Chinese character is composed of several strokes ordered in a particular sequence. The stroke sequence contains useful online information for handwriting recognition and handwriting education. Although there exist some general heuristic stroke sequence rules, sometimes these rules can be inconsistent making it difficult to apply them to determine the standard writing sequence given a set of strokes. In this paper, we proposed a method to estimate the standard writing sequence given the strokes of a Chinese character. The strokes are modeled as discrete states with the state transition costs determined by the result of the classification into forward/backward order of each stroke pair using the positional features. Candidate sequences are found by shortest path algorithm and the final decision of the stroke sequence is made according to the total handwriting energy in case there is more than one candidate sequence. Experiments show that our results provide better performance than existing approaches.
17170661
On finite automata with limited nondeterminism
Abstract. We develop a new algorithm for determining if a given nondeterministic finite automaton is limited in nondeterminism. From this, we show that the number of nondeterministic moves of a finite automaton, if limited, is bounded by 
$2^{n} - 2$ where 
$n$ is the number of states. If the finite automaton is over a one-letter alphabet, using Gohon's result the number of nondeterministic moves, if limited, is less than 
$n^{2}$. In both cases, we present families of finite automata demonstrating that the upper bounds obtained are almost tight. We also show that the limitedness problem of the number of nondeterministic moves of finite automata is PSPACE-hard. Since the problem is already known to be in PSPACE, it is therefore PSPACE-complete.
