Weihua Dai

Chaos and wavelet based colonic motility analysis for subjects with constipation

This paper proposes a method for analyzing the colonic motility of subjects with constipation based on chaos and wavelet. Using a capsule system with an application-specific integrated circuit (ASIC), the pressure data of human colon can be monitored accurately. Preprocessing of colonic pressure signal was performed primarily by applying threshold processing and wavelet de-noising. Then, wavelet with six-layer decomposition was implemented based on Daubechies 5 wavelet basis. Hilbert-Huang transform (HHT) was used for analyzing the frequency spectrum of detail signals. Particularly, six features include the peak frequency of detail signal at level 3, the peak frequency of detail signal at level 4, the Lyapunov index, correlation dimension, Kolmogorov entropy, and box dimension of were extracted for diagnosis purposes based on HHT spectrum and chaos. Moreover, the features space of 20 subjects was used to build the probabilistic neural network (PNN). As a consequence, the classification accuracy of the other 11 subjects based on PNN reached 81.8% in total.

Least-squares estimation for linear models with certain ranges

As a signal processing method, the least-squares method plays a crucial role in parameter estimation, and great progress has been made in recent decades. However, errors may occur when the parameters to be estimated have some actual physical meaning, e.g., if the human-body temperature is estimated to be 70 °C by a general least-squares method. In this study, we consider solving a particular problem, named ranged least-squares estimation (RLSE), where the parameters are restricted to certain meaningful ranges. By using a theoretical analysis, we prove that the solution of the RLSE problem is unique and can be obtained in finite number of steps when the system matrix has a full column rank. Two programmable algorithms are proposed: a basic algorithm and another with improved efficiency. We also present a numerical experiment of an actual RLSE problem for hydrological parameter estimation, which validates the proposed method.

Calibration Method of an Ultrasonic System for Temperature Measurement

System calibration is fundamental to the overall accuracy of the ultrasonic temperature measurement, and it is basically involved in accurately measuring the path length and the system latency of the ultrasonic system. This paper proposes a method of high accuracy system calibration. By estimating the time delay between the transmitted signal and the received signal at several different temperatures, the calibration equations are constructed, and the calibrated results are determined with the use of the least squares algorithm. The formulas are deduced for calculating the calibration uncertainties, and the possible influential factors are analyzed. The experimental results in distilled water show that the calibrated path length and system latency can achieve uncertainties of 0.058 mm and 0.038 μs, respectively, and the temperature accuracy is significantly improved by using the calibrated results. The temperature error remains within ±0.04°C consistently, and the percentage error is less than 0.15%.