Shao-Wei Leu

Near-Shortest Path Planning on a Quadratic Surface With

An O(n log n) near-shortest path-planning algorithm based on the Delaunay triangulation, Ahuja-Dijkstra algorithm, and ridge points in the quadratic plane is presented. The shortest path planning is an NP-hard problem in the general 3-D space. Compared with the other O(n log n) time near-shortest path approach, the path length of the proposed method is 2.81% longer than the Kanai and Suzukis algorithm with 29 Steiner points, but the computation is 4,261 times faster. Notably, the proposed method is ideal for being extended to solve the path-planning problem on the mission planning of cruise missile.

O(n\log n)

This paper proposes an O(nlog n) time algorithm capable of finding near-shortest path on polygonal surfaces. Shortest-path planning in 3-dimensional space is an NP-hard problem. Theoretically, if the number of Steiner points in Kanai and Suzukis algorithm is allowed to approach infinity, the path obtained will be optimal. In practice, the results generated by the KSs algorithm with 29 Steiner points are very close to the optimal solutions. We thus compared the experimental results of our algorithm to the results of the KSs algorithm using 29 Steiner points. Under such configuration, the average path length obtained by our method is slightly longer than the KSs, but our computing time is much shorter. The comparisons indicate that the proposed method is highly efficient for path-planning on polygonal surfaces. The method can be potentially applied to many important research and industrial fields such as 3D route planning, GIS, CNC tooling, etc.

Time

In this paper, the symbol error rate for circular Amplitude-and-Phase Shift Keying (APSK) modulation in linear additive white Gaussian noise (AWGN) channel was theoretical evaluated and a new principle for optimal constellation design was proposed. The new principle can maximize the normalized Euclidean distance and reduce the variation between inter-ring and intra-ring distances for high level M-ary APSK modulation. The simulation results showed that the proposed optimal constellation can achieve lower symbol error rate (SER) than the Quadrature Amplitude Modulation (QAM) constellation.

Shortest path-planning on polygonal surfaces with O (nlog n) time

An adaptive back propagation (BP) neural network based PN code acquisition system is presented. Conventional neural network based acquisition systems are usually trained on PN code, but this system is based on training a back propagation neural network at all possible phases of the output of a correlation detector which is modified by a recursive accumulator. The recursive accumulator can converge the input of the neural network into a limited sample space, and the BP neural network acquires the phase of the received PN code from the converged data. The advantages of this system are that the gain of the system is controllable and the training data sample space is limited. The BP neural network is used to distinguish the transmitted signal and noise. Computer simulations show that the proposed system can acquire the phase of the received PN code correctly at very low signal-to-noise ratio (SNR) in an AWGN channel.

A new principle for circular APSK constellation optimization

This paper proposed a fractal-wavelet (FW) denoising alternative based on applying texture analysis technique to the fractal matching process. Texture has been regarded as a similarity grouping in an image. Roughness is a perceived property to describe the structural texture. This paper applies the roughness entropy fractal dimension (REFD) algorithm to FW coding process, as the REFD FW algorithm, in finding each range subtree for the optimal matched domain subtree according to the best possible minimal differential of texture similarity measurements. It is believed that such measurement would well capture the texture similarity. The REFD FW algorithm denoises a side-scan sonar image in such a way that the parts of noise-free image have to be approximated as well as possible whereas the noisy parts are discarded. The best possible minimal distance between the two REFD values of domain-range subtrees is used to determine which the best approximation is. The minimal similarity distance quantifies the degree of texture similarity between domain-range subtrees. The REFD FW algorithm have been applied to two side-scan sonar images, one is the wreck of M.V. Sea Angel which is taken by the Polaris, Taiwan, and the wreck of a sailing schooner from MSTL, in different configurations to investigate the corresponding quality of the images using two error criteria: mean square error (MSE) and the peak signal to noise ratio (PSNR). The experimental results indicate that the REFD is appropriate as the criteria of determining range-domain matching in FW coder to well approximate the images. We conclude that the REFD FW algorithm is adaptable in denoising side-scan sonar image and that the images are more appealing visually.

Adaptive BP neural network (ABPNN) based PN code acquisition system via recursive accumulator

This study proposed an approach to measure the burstiness of network traffic based on fractal dimensions (FDs). By definition, burstiness is the degree of variation in network traffic. This study defined two types of FDs: (1) the FD of network traffic that describes the flow variation of network traffic, and (2) the FD of the range that describes the degree of flow dispersal. The proposed method uses an adaptive time-slot monitoring mechanism to monitor the network. The relevant FDs are derived from measurements obtained during each time slot in a monitoring window.This study conducted experiments using NS2 simulation data. The experimental results indicate that the proposed method can effectively measure the burstiness of network traffic. The method provides a meaningful way to describe the variation of network traffic and reduces monitoring overhead by using an adaptive time-slot monitoring mechanism.

An efficient sidescan sonar image denoising method based on a new roughness entropy fractal dimension

Burstiness is an important network feature. Many studies apply crude methods using “burst” or flow size to diagnose bursty flows, but these approaches cannot reveal traffic details. Using the self-similarity of network flow, the study transforms the time-domain traffic into space-domain data, and adopts the variations of fractal dimensions to determine the variations of burstiness. The resulting variations of burstiness indicate the irregular situation of network. Experimental results show that the variation of the fractal dimension is proportional to the variation of burstiness. Thus, a variation that exceeds a pre-defined threshold indicates irregular traffic. Triggering a simple alarm upon detecting irregular traffic can ameliorate the following traffic. Therefore, the proposed method is an effective gauge for flow monitoring because it watches the fractal dimensions derived from network traffic. The proposed method can help network administrators monitor traffic in detail and better manage their networks.

Network Burst Monitoring and Detection based on Fractal Dimension with Adaptive Time Slot Monitoring Mechanism

Multicast switches have become indispensible for modern computer networks due to the proliferation of multicast traffic on the Internet. One important issue which greatly affects the performance of a multicast switch is how to reduce data loss caused by blocking during the process of duplication and routing of the packets. This paper proposes a multicast crossbar switch with an inner queue at each cross point. With the proposed architecture, no additional control circuits are needed for performing duplication and self-routing. To reduce data loss, duplicated packets are first stored in the inner queues, then continue to transmit at the beginning of the next time slot. By controlling the interarrival time of two sequential groups of packets, our approach can reduce the rate of data loss to 10−6 or less. Due to simplicity of the proposed architecture, hardware implementation can be realized with ease while delivering good scalability and stackability. The proposed multicast switch has been implemented and verified on an Altera Stratix II EP2S60F1020 chip. It operates at a clock rate of 80 MHz and uses only eight percent of the available look-up tables.

Measurement of flow burstiness by fractal technique

The main drawback of a centralized peer-to-peer (P2P) network is that it can suffer from single-point failures during a over-flooding of requests. On the other hand, a distributed P2P has network congestion problems. In this paper, we propose a hybrid structure based on a mesh-connected tree (MCT) architecture to overcome above situations. The simulation of packet transformation in MCT architecture analyzes delay, jitter and package loss. We find, during a simulated transmission time of 0.001 seconds, the package loss to be 0, while the best peak-to-peak delay time and jitter of the proposed P2P scheme are 0.002217 and 0.00140, respectively. Consequently, the proposed method effectively solves the over-flooding and network congestion in both centralized and distributed P2P networks.