Low Insertion Loss Substrate Integrated Waveguide Quasi–Elliptic Filters for V- Band Wireless Personal Area Network Applications

Novel V-band substrate integrated waveguide (SIW) filters have been presented. Design procedures for the filters synthesis and mechanisms providing quasi-elliptic response have been explained. The insertion loss of the filters has been measured below 2 dB with microstrip-to-SIW transitions being included.

Analyzing laser plasma interferograms with a continuous wavelet transform ridge extraction technique: the method

Laser plasma interferograms are currently analyzed by extraction of the phase-shift map with fast Fourier transform (FFT) techniques [Appl. Opt. 18, 3101 (1985)]. This methodology works well when interferograms are only marginally affected by noise and reduction of fringe visibility, but it can fail to produce accurate phase-shift maps when low-quality images are dealt with. We present a novel procedure for a phase-shift map computation that makes extensive use of the ridge extraction in the continuous wavelet transform (CWT) framework. The CWT tool is flexible because of the wide adaptability of the analyzing basis, and it can be accurate because of the intrinsic noise reduction in the ridge extraction. A comparative analysis of the accuracy performances of them new tool and the FFT-based one shows that the CWT-based tool produces phase maps considerably less noisy and that it can better resolve local inhomogeneties. (C) 2001 Optical Society of America.

Inline Interdigital Pseudo-Elliptic Helical Resonator Filters

A new inline coupling topology for narrowband helical resonator filters is proposed that allows to introduce selectively located transmission zeros (TZs) in the stopband. We show that a pair of helical resonators arranged in an interdigital configuration can realize a large range of in-band coupling coefficient values and also selectively position a TZ in the stopband. The proposed technique dispenses the need for auxiliary elements, so that the size, complexity, power handling and insertion loss of the filter are not compromised. A second order prototype filter with dimensions of the order of 0.05 lambda, power handling capability up to 90 W, measured insertion loss of 0.18 dB and improved selectivity is presented.

AdaBoost Multiple Feature Selection and Combination for Face Recognition

Gabor features have been recognized as one of the most successful face representations. Encouraged by the results given by this approach, other kind of facial representations based on Steerable Gaussian first order kernels and Harris corner detector are proposed in this paper. In order to reduce the high dimensional feature space, PCA and LDA techniques are employed. Once the features have been extracted, AdaBoost learning algorithm is used to select and combine the most representative features. The experimental results on XM2VTS database show an encouraging recognition rate, showing an important improvement with respect to face descriptors only based on Gabor filters.

Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics

In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

Enhanced approach for latent semantic indexing using wavelet transform

Latent semantic indexing (LSI) is a technique used for intelligent information retrieval (IR). It can be used as an alternative to traditional keyword matching IR and is attractive in this respect because of its ability to overcome problems with synonymy and polysemy. This study investigates various aspects of LSI: the effect of the Haar wavelet transform (HWT) as a preprocessing step for the singular value decomposition (SVD) in the key stage of the LSI process; and the effect of different threshold types in the HWT on the search results. The developed method allows the visualisation and processing of the term document matrix, generated in the LSI process, using HWT. The results have shown that precision can be increased by applying the HWT as a preprocessing step, with better results for hard thresholding than soft thresholding, whereas standard SVD-based LSI remains the most effective way of searching in terms of recall value.

Wavelet analysis of bender element signals

Accurate determination of shear wave arrival time using bender elements may be severely affected by a combination of near-field effects and reflected waves. These may mask the first arrival of the shear wave, making its detection difficult in the time domain. This paper describes an approach for measuring the shear wave arrival time through analysis of the output signal in the time-scale domain using a multi-scale wavelet transform. The local maxima lines of the wavelet transform modulus are observed at different scales, and all singularities are mathematically characterised, allowing subsequent detection of the singularity relating to the first arrival. Examples of the use of this approach on typical synthetic and experimental bender element signals are also supplied, and these results are compared with those from other time and frequency domain approaches. The wavelet approach is not affected by near-field effects, but instead is characterised by a relatively consistent singularity related to the shear wave arrival time, across a range of frequencies and noise levels.