Quang M. Tieng

Recognition of 2D object contours using the wavelet transform zero-crossing representation

A new algorithm to recognize a two-dimensional object of arbitrary shape is presented. The object boundary is first represented by a one-dimensional signal. This signal is then used to build the wavelet transform zero-crossing representation of the object. The algorithm is invariant to translation, rotation and scaling. Experimental results show that, compared with the use of Fourier descriptors, our algorithm gives more stable and accurate results.

Wavelet-based affine invariant representation: a tool for recognizing planar objects in 3D space

A technique is developed to construct a representation of planar objects undergoing a general affine transformation. The representation can be used to describe planar or nearly planar objects in a three-dimensional space, observed by a camera under arbitrary orientations. The technique is based upon object contours, parameterized by an affine invariant parameter and the dyadic wavelet transform. The role of the wavelet transform is the extraction of multiresolution affine invariant features from the affine invariant contour representation. A dissimilarity function is also developed and used to distinguish among different object representations. This function makes use of the extrema on the representations, thus making its computation very efficient. A study of the effect of using different wavelet functions and their order or vanishing moments is also carried out. Experimental results show that the performance of the proposed representation is better than that of other existing methods, particularly when objects are heavily corrupted with noise.

Equivalent circuit of a dipole antenna using frequency-independent lumped elements

A four-element lumped-parameter equivalent circuit, consisting of a resistance, an inductance, and two capacitances, has been found to represent the feed-point impedance of a dipole antenna. The values of these elements are related only to the physical dimensions of the antenna, not the frequency of operation. Empirical formulas are given for all the elements. The equivalent circuit gives negligible errors in radiation resistance and reactance for dipole half-lengths less than 0.1 lambda , rising to 1% for resistance and 6% for reactance at 0.25 lambda . It can be readily used in standard computer software packages such as SPICE, PSPICE, and MICROCAP. >

Crowdsourcing reproducible seizure forecasting in human and canine epilepsy

See Mormann and Andrzejak (doi:10.1093/brain/aww091) for a scientific commentary on this article.   Seizures are thought to arise from an identifiable pre-ictal state. Brinkmann et al. report the results of an online, open-access seizure forecasting competition using intracranial EEG recordings from canines with naturally occurring epilepsy and human patients undergoing presurgical monitoring. The winning algorithms forecast seizures at rates significantly greater than chance.

Parameter Estimation of Stochastic Processes with Long‐range Dependence and Intermittency

This paper considers the case where a stochastic process may display both long-range dependence and second-order intermittency. The existence of such a process is established in Anh, Angulo and Ruiz-Medina (1999). We systematically study the estimation of parameters involved in the spectral density function of a process with long-range dependence and second-order intermittency. An estimation procedure for the parameters is given. Numerical results are presented to support the estimation procedure proposed in this paper.

An application of wavelet-based affine-invariant representation

Recently, a novel technique used to construct an affine-invariant representation based on the dyadic wavelet transform was proposed and tested on synthesised 2D contours (Tieng and Boles, 1994). In this paper, the performance of this representation with real objects under perspective transformation is considered. In comparison with a similarity invariant (curvature) representation, experimental results show that the proposed affine-invariant representation is the most appropriate one to represent and recognise objects under perspective transform.

Multifractal analysis of Hong Kong air quality data

This paper describes a multifractal model for representing the high events (intermittency) of air pollution. This model building is the first step toward the development of a cointegration model for prediction of pollution episodes. The method is applied to the time series of two pollutants (NO and SO2) at three locations of the Hong Kong airshed.

Globally optimal superconducting magnets part I: minimum stored energy (MSE) current density map.

An optimal current density map is crucial in magnet design to provide the initial values within search spaces in an optimization process for determining the final coil arrangement of the magnet. A strategy for obtaining globally optimal current density maps for the purpose of designing magnets with coaxial cylindrical coils in which the stored energy is minimized within a constrained domain is outlined. The current density maps obtained utilising the proposed method suggests that peak current densities occur around the perimeter of the magnet domain, where the adjacent peaks have alternating current directions for the most compact designs. As the dimensions of the domain are increased, the current density maps yield traditional magnet designs of positive current alone. These unique current density maps are obtained by minimizing the stored magnetic energy cost function and therefore suggest magnet coil designs of minimal system energy. Current density maps are provided for a number of different domain arrangements to illustrate the flexibility of the method and the quality of the achievable designs.

Recognition of 2D objects from the wavelet transform zero-crossing representation

Wavelet theory provides very general techniques that can be utilized to perform many tasks in signal and image processing applications. The zero-crossings of a wavelet transform of a signal, using a particular class of wavelets, provide the locations of the sharp variation points of the signal at the different resolutions. These points provide meaningful features for characterizing the signals. In this paper, we present a new approach to recognize a 2D object of general shape based on its wavelet transform zero-crossing representation. This is performed in two stages. The first stage consists of building a 1D signal representation of the 2D boundary of the object followed by obtaining the zero-crossing of the wavelet transform of the resulting representation. The second stage is the matching procedure for object recognition. Our algorithm uses only a few intermediate resolution levels for matching thus making it computationally efficient while being less sensitive to noise and quantization errors. A normalization process is implemented for matching objects of different scales to their models both in noisy and noise-free situations. Our algorithms have been tested using simulated object boundaries and have been successful in recognizing the objects with results being invariant under translation, rotation and scaling.

Stochastic models for fractal processes

This paper considers the situation where a stochastic process may display both long-range dependence (LRD) and intermittency. The existence of such a process is established in Anh et al. (1999). Existing works have commonly paid attention either to LRD or intermittency quite separately. This paper offers a convenient framework to study both effects simultaneously. A method is given to estimate and separate the two effects. The wavelet theory plays an essential role in this procedure. Numerical experiments on fractional Brownian motion and multiplicative cascade processes confirm the power of the method.