This Master´s thesis discuses the protection of data transmission against long error bursts. The data is transmited throught the channel with defined error rate. Parameters of the channel are error-free interval 2000 bits and length of burst error 250 bits. One of the aims of this work is to make a set of possible methods for the realization of a system for data correction. The basic selection is made from most known codes. These codes are divided into several categories and then the best one is chosen for higher selection. Of course interleaving is used too. Only one code from each category can pass on to the higher level of the best code selection. At the end the codes are compared and the best three are simulated using the Matlab program to check correct function. From these three options, one is chosen as optimal regarding practical realization. Two options exist, hardware or software realization. The second one would seem more useful. The real codec is created in validator language C. Nowadays, considering language C and from a computer architecture point of view the 8 bits size of element unit is convenient. That´s why the code RS(255, 191), which works with 8 bits symbols, is optimal. In the next step the codec of this code is created containing the coder and decoder of the code above. The simulation of error channel is ensured by last program. Finally the results are presented using several examples.

The theoretical contents of this thesis are studies of overcomplete models. Those are the models of signals, on which is set for their parametrization more variables, than it's necessary and consequently there's computed so-called sparse solution via iteration algorithms. A goal of this analysis is a selection just of the considerable (sparse) parameters. The theory is based on a linear algebra, vector spaces, bases and so-called frames. The task of the individual project of this thesis is a description and simulation of two speech coders: a classical coder based on linear predictive speech coding and a coder, that's making use of overcomplete stochastic ARMA processes models. A part of their realization is to simulate their decoders and a analyze their reconstruction quality. For their realization there is used MATLAB and an overcomplete models' library (toolbox frames).

At the beginning is diploma thesis focused on a distribute power line parameters measurement and examination changes of this parameters depending on using of various power line cables. On the basis of measurements is made a transmission channel in Matlab & Simulink, where are executed simulations with power transmission line. The simulated power line is based on measured distribute parameters or physical proportions of cabels. By changing different parts of simulated communication channel is a symbol error rate expressed on the lenght of transmission line.

An innate desire of many vision researchers IS to unravel the mystery of human visual perception Such an endeavor, even ~f it were not wholly successful, is expected to yield byproducts of considerable significance to industrial applications Based on the current understanding of the neurophysiological and computational processes in the human bran, it is believed that visual perception can be decomposed into distinct modules, of which feature / contour extraction and recognition / classification of the features corresponding to the objects play an important role. A remarkable characteristic of human visual expertise is its invariance to rotation shift, and scaling of objects in a scene Researchers concur on the relevance of imitating as many properties as we have knowledge of, of the human vision system, in order to devise simple solutions to the problems in computational vision. The inference IS that this can be more efficiently achieved by invoking neural architectures with specific characteristics (similar to those of the modules in the human brain), and conforming to rules of an appropriate mathematical baas As a first step towards the development of such a framework, we make explicit (1) the nature of the images to be analyzed, (11) the features to be extracted, (111) the relationship among features, contours, and shape, and (iv) the exact nature of the problems To this end, we formulate explicitly the problems considered in this thesis as follows Problem 1 Given an Image localize and extract the boundary (contours) of the object of Interest in lt Problem 2 Recognize the shape of the object characterized by that contour employing a suitable coder-recognizer such that ~t IS unaffected by rotation scaling and translation of the objects Problem 3 Gwen a stereo-pair of Images (1) extract the salient contours from the Images, (ii)establish correspondence between the points in them and (111) estimate the depth associated with the points We present a few algorithm as practical solutions to the above problems. The main contributions of the thesis are: • A new algorithm for extraction of contours from images: and • A novel method for invariantly coding shapes as pulses to facilitate their recognition. The first contribution refers to a new active contour model, which is a neural network designed to extract the nearest salient contour in a given image by deforming itself to match the boundary of the object. The novelty of the model consists in the exploitation of the principles of spatial isomorphism and self organization in order to create flexible contours characterizing shapes in images. It turns out that the theoretical basis for the proposed model can be traced to the extensive literature on: • Gestalt perception in which the principles of psycho-physical isomorphism plays a role; and • Early processing in the human visual system derived from neuro-anatomical and neuro-physiological properties. The initially chosen contour is made to undergo deformation by a locally co-operative, globally competitive scheme, in order to enable it to cling to the nearest salient contour in the test image. We illustrate the utility and versatility of the model by applying to the problems of boundary extraction, stereo vision, and bio-medical image analysis (including digital libraries). The second contribution of the thesis is relevant to the design and development of a machine vision system in which the required contours are first to be extracted from a given set of images. Then follows the stage of recognizing the shape of the object characterized by that contour. It should, however, be noted that the latter problem is to be resolved in such a way that the system is unaffected by translation, relation, and scaling of images of objects under consideration. To this end, we develop some novel schemes: • A pulse-coding scheme for an invariant representation of shapes; and • A neural architecture for recognizing the encoded shapes. The first (pulse-encoding) scheme is motivated by the versatility of the human visual system, and utilizes the properties of complex logarithmic mapping (CLM) which transforms rotation and scaling (in its domain) to shifts (in its range). In order to handle this shift, the encoder converts the CLM output to a sequence of pulses These pulses are then fed to a novel multi-layered neural recognizer which (1) invokes template matching with a distinctly implemented architecture, and (11) achieves robustness (to noise and shape deformation) by virtue of its overlapping strategy for code classification The proposed encoder-recognizer system (a) is hardware implementable by a high-speed electronic switching circuit, and (b) can add new patterns on-line to the existing ones Examples are given to illustrate the proposed schemes. The them is organized as follows: Chapter 2 deals with the problem of extraction of salient contours from a given gray level image, using a neural network-based active contour model It explains the need for the use of active contour models, along with a brief survey of the existing models, followed by two possible psycho-physiological theories to support the proposed model After presenting the essential characteristics of the model, the advantages and applications of the proposed approach are demonstrated by some experimental results. Chapter 3 is concerned with the problem of coding shapes and recognizing them To this end, we describe a pulse coder for generating pulses invariant to rotation, scaling and shift The code thus generated IS then fed to a recognizer which classifies shapes based on the pulse code fed to it The recognizer can also add new shapes to its 'knowledge-base' on-line. The recognizer's properties are then discussed, thereby bringing out its advantages with respect to various related architectures found in the literature. Experimental results are then presented to Illustrate some prominent characteristics of the approach. Chapter 4 concludes the thesis, summarizing the overall contribution of the thesis, and describing possible future directions

The unprecedented turbulence and uncertainty experienced in global economic and financial markets because of the 'credit crunch' has had a damaging impact on consumer confidence. Trust and credibility have been eroded as many customers feel let down by the banks suggesting the need for banks to rebuild constructive dialogue and long-term, meaningful relationships with their customers again. Though financial service, in this case, is considered a utilitarian service, based on the fact that money is needed to support people‘s daily activities, the present state of financial service has suggested the need for banks to appeal to consumers‘ emotions with the aim of improving their reputation. Also, the competition within the industry also could suggest the need to adopt an emotionally appealing advertisement strategy as emotions are known to play an influential role in building robust brand preference. This study builds on the communication theory, meaning transfer theory and consumer involvement theory, to understand the messages the banks are sending out and to elicit consumers‘ emotional reaction. One thousand, two hundred and seventy-four UK bank advertisements in nine national newspapers were content-analysed to identify the emotional appeals presented by the banks. The perception of these appeals and their associated meanings were sought through semi-structured interviews with 33 participants in London and Luton. The results of the analysis indicated that UK Banks are utilising emotional appeal in their advertisements to reach out to the consumers to convince them to upgrade their account, to open an additional account or switch their account. The most predominantly used appeals were relief and relaxation followed by excitement and happiness or satisfaction with the bank, and finally, security and adventure. However, variations were found in different financial products that employed emotional appeals. It was found that high-involvement products such as mortgages and loans used fewer emotional appeals. Both bank groups - high street banks, including the big four (Barclays, HSBC, Lloyds and RBS) and non-high street banks, such as the new entrants, supermarket brands, and online banks were using emotional appeals. However, it is acknowledged that the communication strategies between these banks could be different as the non-high street banks are more likely to repeat and publish the same messages across many newspapers, instead of publishing different emotionally appealing advertisements. Though consumers acknowledged these emotional appeals in the advertisements, they were more concerned about their relationship with the banks as they don‘t rely on advertisements to make a financial decision. Rather, recommendations from families, friends and associates and also branch location are more important when deciding on which bank to choose. The lack of congruency between financial services and emotional appeals in advertisements is also observed as customers are more likely to be persuaded by rational appeals however this study has not completely ruled out emotional appeals in bank advertisements as the use of both types of appeals is recommended. The study provides important theoretical and managerial contributions to understanding how the consumers understand meaning-embedded advertisements produced by the banks. Managers will be able to consider the implications of advertisements in enhancing their brand equity and building relationships with customers in anticipation that, by word of the mouth and established relationship, their bank‘s reputation will be enhanced. Limitations of the study and opportunities for future research are identified.