Compressed sensing is a recently developed technique that exploits the sparsity of naturally occurring signals and images to reduce the volume of the data using less number of samples, computing the sparsity of the signal. In the traditional/conventional approaches the images are acquired and compressed, where as compressed sensing aims to acquire the “compressed signals” with few numbers of sa...

To accurately diagnose the mechanical failure of the fan, two diagnostic methods based on the wavelet packet energy feature and sample entropy feature are proposed. Vibration signals acquisition of 13 kinds of running states are achieved on the 4-73 No. 8D centrifugal fan test bench. The wavelet packet energy feature vector of each vibration signal is rapidly extracted through the wavelet packe...

In view of the growing use of automatic speech recognition in the modern society, we study various alternative representations of the speech signal that have the potential to contribute to the improvement of the recognition performance. Specifically, the main targets of the present article are to overview and evaluate the practical importance of some recently proposed, and thus less studied, wa...

Surface characterization plays a significant role in evaluating surface functional performance. In this paper, we introduce wavelet packet transform for surface roughness characterization and surface texture extraction. Surface topography is acquired by a confocal laser scanning microscope. Smooth border padding and de-noise process are implemented to generate a roughness surface precisely. By ...

A fast rate-distortion (R-D) optimized wavelet packet (WP) transform is proposed for image compression in this research. By analyzing the R-D performance of the quantizer and the entropy coder, we show that the coding distortion D can be modeled as an exponentially decaying function as the coding rate R increases. With this exponential R-D model, it is proved that the constant R-D slope criteri...

For the purpose of successfully developing a prosthetic control system, many attempts have been made to improve the classification accuracy of surface electromyographic (SEMG) signals. Nevertheless, the effective feature extraction is still a paramount challenge for the classification of SEMG signals. The relative frequency band energy (RFBE) method based on wavelet packet decomposition was pro...

Abstract: At present, the research is still in the primary stage in the process of fault disturbance energy transfer in the multilevel modular converter based high voltage direct current (HVDC-MMC). An urgent problem is how to extract and analyze the fault features hidden in MMC electrical information in further studies on the HVDC system. Aiming at the above, this article analyzes the influenc...

Andre Guntoro, Manfred Glesner. A Lifting-Based Discrete Wavelet Transform and Discrete Wavelet Packet Processor with Support for Higher Order Wavelet Filters. Christian Piguet; Ricardo Reis; Dimitrios Soudris. VLSI-SoC: Design Methodologies for SoC and SiP, 313, Springer, pp.154-173, 2010, IFIP Advances in Information and Communication Technology, 978-3-64212266-8. <10.1007/978-3-642-12267-5 9...

The reliable transmission of compressed images across noisy transmission channels and networks prone to packet losses is considered. The problem is viewed from a source coding perspective, where the main constraints are maximum coding efficiency and minimum redundancy. Error-resilient mechanisms are incorporated into wavelet-based image encoding schemes to obtain robust data streams that withst...

The partitioning of turbulent perturbations into a ‘‘low-dimensional’’ active part responsible for much of the turbulent energy and fluxes and a ‘‘high-dimensional’’ passive part that contributes little to turbulent energy and transport dynamics is investigated using atmospheric surface-layer (ASL) measurements. It is shown that such a partitioning scheme can be achieved by transforming the ASL...