Seismic signal processing via the ILLIAC IV computer,

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Design of MIMO testbed with an FPGA board for fast signal processing

This paper describes the design of a Multiple Input Multiple Output testbed for assessing various MIMO transmission schemes in rich scattering indoor environments. In the undertaken design, a Field Programmable Gate Array (FPGA) board is used for fast processing of Intermediate Frequency signals. At the present stage, the testbed performance is assessed when the channel emulator between transmitter and receiver modules is introduced. Here, the results are presented for the case when a 2x2 Alamouti scheme for space time coding/decoding at transmitter and receiver is used. Various programming details of the FPGA board along with the obtained simulation results are reported

Adaptive Signal Processing for Power Line Communications

This thesis represents a significant part of the research activity conducted during the PhD program in Information Technologies, supported by Selta S.p.A, Cadeo, Italy, focused on the analysis and design of a Power Line Communications (PLC) system. In recent times the PLC technologies have been considered for integration in Smart Grids architectures, as they are used to exploit the existing power line infrastructure for information transmission purposes on low, medium and high voltage lines. The characterization of a reliable PLC system is a current object of research as well as it is the design of modems for communications over the power lines. In this thesis, the focus is on the analysis of a full-duplex PLC modem for communication over high-voltage lines, and, in particular, on the design of the echo canceller device and innovative channel coding schemes.

Analysis of computer communication systems by use of digital signal processing methods

Queueing theory is an effective tool in the analysis of canputer camrunication systems. Many results in queueing analysis have teen derived in the form of Laplace and z-transform expressions. Accurate inversion of these transforms is very important in the study of computer systems, but the inversion is very often difficult. In this thesis, methods for solving some of these queueing problems, by use of digital signal processing techniques, are presented. The z-transform of the queue length distribution for the Mj GY jl system is derived. Two numerical methods for the inversion of the transfom, together with the standard numerical technique for solving transforms with multiple queue-state dependence, are presented. Bilinear and Poisson transform sequences are presented as useful ways of representing continuous-time functions in numerical computations.

Signal processing techniques for ultrasonic inspection

This thesis discusses the need for nondestructive testing and highlights some of the limitations in present day techniques. Special interest has been given to ultrasonic examination techniques and the problems encountered when they are applied to thick welded plates. Some suggestions are given using signal processing methods. Chapter 2 treats the need for nondestructive testing as seen in the light of economy and safety. A short review of present day techniques in nondestructive testing is also given. The special problems using ultrasonic techniques for welded structures is discussed in Chapter 3 with some examples of elastic wave propagation in welded steel. The limitations in applying sophisticated signal processing techniques to ultrasonic NDT~ mainly found in the transducers generating or receiving the ultrasound. Chapter 4 deals with the different transducers used. One of the difficulties with ultrasonic testing is the interpretation of the signals encountered. Similar problems might be found with SONAR/RADAR techniques and Chapter 5 draws some analogies between SONAR/RADAR and ultrasonic nondestructive testing. This chapter also includes a discussion on some on the techniques used in signal processing in general. A special signal processing technique found useful is cross-correlation detection and this technique is treated in Chapter 6. Electronic digital compute.rs have made signal processing techniques easier to implement -Chapter 7 discusses the use of digital computers in ultrasonic NDT. Experimental equipment used to test cross-correlation detection of ultrasonic signals is described in Chapter 8. Chapter 9 summarises the conclusions drawn during this investigation.

Signal processing in a loudspeaking telephone

One of the major problems associated with communication via a loudspeaking telephone (LST) is that, using analogue processing, duplex transmission is limited to low-loss lines and produces a low acoustic output. An architectural for an instrument has been developed and tested, which uses digital signal processing to provide duplex transmission between a LST and a telopnone handset over most of the B.T. network. Digital adaptive-filters are used in the duplex LST to cancel coupling between the loudspeaker and microphone, and across the transmit to receive paths of the 2-to-4-wire converter. Normal movement of a person in the acoustic path causes a loss of stability by increasing the level of coupling from the loudspeaker to the microphone, since there is a lag associated the adaptive filters learning about a non-stationary path, Control of the loop stability and the level of sidetone heard by the hadset user is by a microprocessoe, which continually monitors the system and regulates the gain. The result is a system which offers the best compromise available based on a set of measured parameters.A theory has been developed which gives the loop stability requirements based on the error between the parameters of the filter and those of the unknown path. The programme to develope a low-cost adaptive filter in LST produced a low-cost adaptive filter in LST produced a unique architecture which has a number of features not available in any similar system. These include automatic compensation for the rate of adaptation over a 36 dB range of output level, , 4 rates of adaptation (with a maximum of 465 dB/s), plus the ability to cascade up to 4 filters without loss o performance. A complex story has been developed to determine the adptation which can be achieved using finite-precision arithmatic. This enabled the development of an architecture which distributed the normalisation required to achieve optimum rate of adaptation over the useful input range. Comparison of theory and measurement for the adaptive filter show very close agreement. A single experimental LST was built and tested on connections to hanset telephones over the BT network. The LST demonstrated that duplex transmission was feasible using signal processing and produced a more comfortable means of communication beween people than methods emplying deep voice-switching to regulate the local-loop gain. Although, with the current level of processing power, it is not a panacea and attention must be directed toward the physical acoustic isolation between loudspeaker and microphone.

All-optical signal regeneration by temporal slicing of nonlinearly flattened optical waveform

A novel all-optical time domain regeneration technique using nonlinear pulse broadening and flattening in normal dispersion fiber and subsequent temporal slicing by an amplitude modulator (or a device performing a similar function) is proposed. Substantial suppression of the timing jitter of jitter-degraded optical signals is demonstrated using the proposed approach.

Novel speech signal processing algorithms for high-accuracy classification of Parkinson's disease

There has been considerable recent research into the connection between Parkinson's disease (PD) and speech impairment. Recently, a wide range of speech signal processing algorithms (dysphonia measures) aiming to predict PD symptom severity using speech signals have been introduced. In this paper, we test how accurately these novel algorithms can be used to discriminate PD subjects from healthy controls. In total, we compute 132 dysphonia measures from sustained vowels. Then, we select four parsimonious subsets of these dysphonia measures using four feature selection algorithms, and map these feature subsets to a binary classification response using two statistical classifiers: random forests and support vector machines. We use an existing database consisting of 263 samples from 43 subjects, and demonstrate that these new dysphonia measures can outperform state-of-the-art results, reaching almost 99% overall classification accuracy using only ten dysphonia features. We find that some of the recently proposed dysphonia measures complement existing algorithms in maximizing the ability of the classifiers to discriminate healthy controls from PD subjects. We see these results as an important step toward noninvasive diagnostic decision support in PD.