Korean Character Recognition Using Neural Networks

We present a neural-network approach for recognizing printed Korean characters. Our approach is based on a variant of the back-propagation algorithm. The results indicate that by transforming the character data into Hough space, we can achieve excellent recognition

Generation of a Wide-Band Response Using Early-Time and Middle-Frequency Data Throught the Use of Orthogonal Fuctions

Abstract|Generation of a wide-band response using partial information from the time domain (TD) data and frequency domain (FD) data has been accomplished in this paper through the use of three different orthogonal functions, such as the continuous Laguerre functions, the Bessel-Chebyshev functions, and the associate Hermite functions. In this hybrid approach, one can generate the early-time response using the method of marching-on-in-time (MOT) and use the method of moment (MOM) to generate the middle-frequency response, as the low-frequency data may be unstable. Since the early-time and the middle-frequency data are mutually complimentary, they can provide the missing low- and high-frequency response and the late- time response, respectively. Even though obtaining middle-frequency response from an object needs more computation time than the low- frequency response, this approach has better performance for the interpolation and extrapolation of a wide-band response

Spectrum analysis from nonuniformly sampled data for applications in multiple PRI radar system

This dissertation addresses the problem of the spectrum analysis from nonuniformly sampled data for applications in multiple PRF radar system. The benefits of using a direct spectrum analysis using nonuniformly spaced data instead of using a FFT based CR (Chinese Remainder) theorem have been presented. Using a spectrum analysis based on nonuniformly spaced data, the blind bursts that the target frequency is folded into the clutter band could be overcome easily. This method can also be efficient when there exist multiple interferences with the same magnitude as the target. The objective of this research is to find a suitable and efficient method for spectrum analysis and for application to the multiple PRF system. To obtain the spectrum from nonuniformly sampled data, seven methods have been investigated and compared with each other. A single example was shown at the end of each approach to test the applicability. The numerical examples have been divided into three parts with respect to the sampling frequency since all the methods operate by different characteristics. To test robustness to the noise, AWGN has been added to the signal and simulated for different cases

Estimation of Azimuth Angle Using an Ultrasonic Sensor for Automobile

A typical ultrasonic sensor has a major lobe that extends beyond 45 degrees. Because the wide beam of the ultrasonic sensor’s main lobe, which is used for straightforward distance measurement, has a low angular resolution, conventional methods such as incidence angle and linear angle measurements cannot accurately determine the azimuthal angle. Determining whether one or more objects are present in a single beam is also challenging. In this study, the azimuthal angles of two or more objects placed beneath a single beam are determined by the Doppler frequency shift. An ultrasonic sensor is mounted on an automobile to transmit and receive an ultrasound when the car moves towards stationary objects. The sensor picks up the object’s reflected Doppler shift signal. The azimuth angle of the objects is determined by estimating the received Doppler shift signal using a standard signal processing method. Near-field motion detection systems and autonomous driving heavily rely on the ability to evaluate the azimuthal angle of objects in a vehicle’s surroundings using the Doppler Effect. These are examples of low-cost technology and active safety, which the experimental results support. Based on the results and error estimation, there is an average error of less than 3% between measured and computed values

Matrix Pencil Method Using Fourth-Order Cumulant

Introduction In recent years, higher order cumulant-based methods, such as fourth-order cumulant, have received increasing interest due to their advantage over secondorder statistics. The Matrix Pencil method(MPM) can be used when the received signals of arrays are approximated by sums of complex exponentials In this paper, we applied the fourth-order cumulant to the Matrix Pencil method. By substituting the fourth-order cumulant of the original array input data the Gaussian additive noise to the signals can be suppressed. The average of conventional MPM has been compared to the proposed method. Simulation result shows that the fourth-order cumulant method generates better performance in finding DOA than the conventional MPM