Statistically more test samples obtained from a single chip would give a better picture of the various noise processes present. Increasing the number of samples while testing one chip would however lead to an increase in the testing time, decreasing the overall throughput. The aim of this report is to investigate the detection of non-Gaussian noise (burst noise) in a random set of data with a small number of samples. In order to determine whether a given set of noise samples has non-Gaussian noise processes present, a Chi-Squared ‘Goodness of Fit’ test on a modeled set of random data is presented. A discussion of test methodologies using a single test measurement pass as well as two passes is presented from the obtained simulation results. / text

Low-density parity-check (LDPC) codes provide excellent error correction performance and can approach the channel capacity, but their performance degrades significantly in the presence of burst noise. Bursts of errors occur in many common channels, including the magnetic recording and the wireless communications channels. Strategies such as interleaving have been developed to help compensate for bursts errors. These techniques do not exploit the correlations that can exist between the noise variance on observations in and out of the bursts. These differences can be exploited in calculations of prior probabilities to improve accuracy of soft information that is sent to the LDPC decoder. Effects of using different noise variances in the calculation of prior probabilities are investigated. Using the true variance of each observation improves performance. A novel burst detector utilizing the forward/backward algorithm is developed to determine the state of each observation, allowing the correct variance to be selected for each. Comparisons between this approach and existing techniques demonstrate improved performance. The approach is generalized and potential future research is discussed.

This thesis explores the issue of noise in the simultaneous interpreting process, using the concept of noise as defined in information theory and the model of communication developed by Claude Shannon. The theoretical section of this thesis first offers a brief explanation of the basic concepts involved in information theory, followed by a description of Shannon's model. Selected models of interpreting are then introduced based on this model of communication. A list of potential types of noise is then presented based on the literature examined that may have an impact on the interpreter during simultaneous interpreting. The empirical section of this thesis consists of a questionnaire and an experiment. The questionnaire determines to what extent interpreters find the potential types of noise from the list created in the theoretical section disruptive in their work. The list of types of noise is also expanded based on respondents' answers. The questionnaire also determines what strategies respondents employ to overcome adverse factors. The new types of noise and strategies employed are described in this thesis using open-ended answers from the respondents. The experiment tests the impact of a burst-noise channel on simultaneous interpreting. A total of 13 respondents took part in the experiment,...

The master’s thesis deals with the noise diagnostic in the solar cells. Describes the main kinds of noises. The samples were quality and reliability screened using noise reliability indicators. The samples were surveyed by measuring the I-V characteristics, the noise spectral density as a function of forward voltage and frequency. It was calculated the noise spectral density as a function of forward current.