Iulian C. Vizitiu

The synthesis of some NLFM laws using the stationary phase principle

In radar literature, the sidelobes reduction techniques using synthesis of some proper nonlinear FM (NLFM) laws represents a major scientific research direction. Accordingly, in order to assure the sidelobes suppression, the main objective of this paper is to present an adequate synthesis algorithm of some NLFM laws based on stationary phase principle. The achieved experimental results confirm a significant sidelobes reduction (i.e., more than -40 dB) without necessity to apply some weighting techniques. Finally, the analysis of the synthesized NLFM laws by ambiguity function tool was also discussed.

Theoretical and practical implementation of scrambling algorithms for speech signals

The problem of secure information transmission over an unsecured medium is very important in the communication systems and especially in the military systems. Speech scrambling is one of the methods used to prevent unauthorized decryption of the message. In this paper three scrambling techniques are presented and their performances are analyzed. These methods were tested based on some real audio signals that they were recorded in an anechoic chamber.

Sidelobes reduction using frequency predistortioning techniques on LFM signals

In the high resolution radar theory, a lot of powerful sidelobes reduction techniques are indicated. Belonging to this major research direction, the goal of this paper is to present some theoretical and experimental results achieved by applying on a LFM radio pulse with the low values of the basis, of the temporal frequency predistortioning techniques at the pulse ends using two proper nonlinear laws. Finally, some aspects concerning the optimization of the parameters assigned to the proposed frequency predistortioning laws are also discussed.

Analysis of direct current nonlinear electrical circuits by means of symbolic computation and genetic algorithms

The paper presents a method for the determination of the bias point of nonlinear electrical circuits, based on the modified nodal method, by utilization of symbolic computation and genetic algorithms. For the solving of the circuit it is written the equations system corresponding to the modified nodal method in a partial symbolic form. On the basis of the partial symbolic form of these equations an error function is generated which gives the circuit solution by minimization. In the paper are presented a few examples of circuits, for which iterative solving is not convergent. These circuits could be solved by means of the elaborated method.

An improved neural approach of Sammon projection algorithm

According to the pattern recognition theory, a very important stage into a classification chain is represented by the feature selection. Although in literature a lot of feature selection techniques are indicated, one of the most important methods as application area is focused on Sammon projection algorithm use. Consequently, in this paper an improved neural approach of Sammon mapping is described. In addition, using a real HRR classification task, a comparison as performance level of the proposed method with other well-known neural versions of Sammon projection technique is also included.