Roland Priemer

Simplicity based gating of heart sounds

Segmentation of the phonocardiogram (PCG) into its major sound components is the first step in automated diagnosis of cardiac abnormalities. Almost all the existing PCG segmentation algorithms are based upon amplitude or frequency characteristics, of the heart sounds, that vary from one cardiac cycle to the other and across different patients. The objective of this work is to provide an efficient PCG segmentation technique, under difficult recording situations, by utilizing the underlying complexity of the dynamical system (heart) giving rise to the heart sound. Complexity based segmentation is invariant to amplitude and frequency variations of the heart sound and yields better time gates for pathological heart sounds.

An Amplitude Modulated Stereo System

An amplitude modulated stereophonic system, which is compatible with conventional monophonic AM systems, is presented in this paper. First, conditions on the envelope and phase function for the transmitted signal are derived. Then, a compatible quadrature AM(compatible QUAM) system is proposed for the transmission and reception of stereophonic program material. Some results of testing the proposed system are included.

Microprocessor based digital signal processing system.

Abstract A microprocessor based digital signal processing system is presented in this paper. The software developed for this system enables the user to easily specify any kind of a digital filter for realtime operation. As demonstrated by a sample hardware design and implementation, low-cost dedicated applications are now feasible.

Compound noise analysis in digital circuits using blind source separation

In the past decade there have been significant efforts to analyze and solve signal integrity issues in pre-nanometer circuits. However, most of these techniques apply to single noise source, and cannot take into account the evolving reality of multiple noise sources interacting with each other. With the scaling of the technology into nanometer regime, maintaining historical rate of performance and signal integrity have become very challenging due to compound noise effects. Noise measurement made at an evaluation node will reflect the cumulative effect of all the active noise sources, while individual and relative severity of various noise sources will determine what types of remedial steps can be adopted, pressing the need for the development of algorithms that study the cumulative noise effects, and analyze the relative contributions of different noise sources. This paper presents a novel method to analyze the characteristics of compound noise effect in very high performance integrated circuits. The algorithm extracts the time characteristics of individual noise sources from the measured voltage in order to study the contribution of each source separately, by applying the technique of blind source separation, which is based on the assumption that the different sources of noise are statistically independent over time. The estimated noise sources can aid in timing and spectral analysis and yield better design techniques

Automatic step size adjustment of the two-dimensional LMS algorithm

This paper gives a method for distinguishing the states of the two dimensional LMS algorithm as it enhances an image in an area having high contrast variations or in an area having low contrast variations. This capability is used to automatically adjust the algorithm step size to improve image enhancement as the degree of contrast variation changes over an entire image.

Adaptive classifiers using ontogenetic neural networks with feedback

The authors give the results of software simulation of Hebbian (D. O. Hebb, 1949) associative learning. Ontogenesis in feedback neural networks similar to those devised by Hopfield implies an initial structure and a plan for associative learning with growth. Experimental results are given to show that the advantages of ontogenetic neural networks configured as adaptive classifiers include rapid adaptation, good performance in classifying correctly, and the ability to cope with high levels of noise in training and operation.<<ETX>>

Regular iterative algorithm for extracting all trees of a linear graph

A regular iterative algorithm (RIA) to extract all trees of a linear graph is presented. The algorith is developed from a sequential algorithm that operates on the incidence matrix of a graph. This RIA can be used to design a processor array that can find trees of a graph at a rate that is independent of the number of graph edges. The RIA is the basis for a processor array that finds one tree of a graph in O(N) time, where N is the number of graph vertices.<<ETX>>

Matlab for electrical and computer engineering students and professionals : with Simulink

This book combines the teaching of the MATLAB® programming language with the presentation and development of carefully selected electrical and computer engineering (ECE) fundamentals. This is what distinguishes it from other books concerned with MATLAB®: it is directed specifically to ECE concerns. Students will see, quite explicitly, how and why MATLAB® is well suited to solve practical ECE problems. This book is intended primarily for the freshman or sophomore ECE major who has no programming experience, no background in EE or CE, and is required to learn MATLAB® programming. It can be used for a course about MATLAB® or an introduction to electrical and computer engineering, where learning MATLAB® programming is strongly emphasized. A first course in calculus, usually taken concurrently, is essential. The book will also serve EE or CE professionals who need to learn MATLAB® and who prefer learning via examples directly relevant to their work. The distinguishing feature of this MATLAB® book is that about 15 per cent develops ECE fundamentals gradually, from very basic principles. Because these fundamentals are interwoven throughout, MATLAB® can be applied to solve relevant, practical problems. The plentiful, in-depth example problems to which MATLAB® is applied were carefully chosen so that results obtained with MATLAB® also provide insights about the fundamentals.

Multireselution quantization-based image watermarking

Illegal duplication and distribution of digital multimedia content over the Internet has been prevalent over the past years. Commercial businesses face millions of dollars in lost revenue each year due to these activities. The traditional approach to data protection is to apply encryption and scrambling. However, these methods alone are not adequate to provide complete content-protection since they cannot protect the data once it has been decrypted and descrambled. A recent technique called digital watermarking is proposed as a complementary approach to cryptography. Digital watermarking is a process in which security or authentication data is imperceptibly embedded within the host data. In this paper, we propose a robust blind image watermarking algorithm for embedding a binary watermark sequence under the wavelet domain. This algorithm demonstrates robustness to some common watermark distortions, or attacks, such as lowpass filtering, JPEG compression, and additive Gaussian noise. Performance comparisons are also given with respect to other robust algorithms.

Separation of Individual Noise Sources from Compound Noise Measurements in Digital Circuits

Analysis of individual noise sources in pre-nanometer circuits cannot take into account the evolving reality of multiple noise sources interacting with each other. Noise measurement made at an evaluation node will reflect the cumulative effect of all the active noise sources, while individual and relative severity of various noise sources will determine what types of remedial steps can be taken, pressing the need for development of algorithms that can analyze the contributions of different noise sources when a noise measurement is available. This paper presents a method to extract the time characteristics of individual noise sources from the measured voltage in order to study the contribution of each source separately, by applying the technique of blind source separation, which is based on the assumption that the different sources of noise are statistically independent over time. The estimated noise sources can aid in timing and spectral analysis and yield better design techniques