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This thesis describes the construction and implementation of a microprocessor controlled recursive adaptive filter applied as a noise canceller. It describes the concept of the adaptive noise canceller, a method of estimating the received signal corrupted with additive interference (noise). This canceller has two inputs, the primary input containing the corrupted signal and the reference input consisting of the additive noise correlated in some unknown way to the primary noise. The reference input is filtered and subtracted from the primary input without degrading the desired components of the signal. This filtering process is adaptive and based on Widrow-Hoff Least-Mean-Square algorithm. Adaptive filters are programmable and have the capability to adjust their own parameters in situations where minimum piori knowledge is available about the inputs. For recursive filters, these parameters include feed-forward (non-recursive) as well as feedback (recursive) coefficients. A new design and implementation of the adaptive filter is suggested which uses a high speed 68000 microprocessor to accomplish the coefficients updating operation. Many practical problems arising in the hardware implementation are investigated. Simulation results illustrate the ability of the adaptive noise canceller to have an acceptable performance when the coefficients updating operation is carried out once every N sampling periods. Both simulation and hardware experimental results are in agreement.

Deliver message by voice is the most important, effective and common method of exchange information for mankind. Language is human specific features and human voice is commonly used tool which is also the important way to pass information to each other. The voice has large information capacity. So we can use modern method to study voice processing technology, so that people can easily transmit, store, access and apply the voice. In this thesis, we designed a collection system that can collect voice and use different filters to filter the noise. After filtering the noise, the voice will be more quality in mobile communication, radio, TV and so on. In this thesis we use Microsoft recorder to collect a voice, and then analyze its time-domain, the frequency spectrum and the characteristics of the voice signal. We use MATLAB‟s function to remove the noise which has been added to the voice, further use bilinear transformation method to design a filter which is based on Butterworth simulation and window function and then filter the voice signal which has been added noise. After that we compare the time-domain and frequency-domain of the original voice and noised voice, then playback the noised voice and de-noising voice and then compare the application of signal processing in FIR filter and IIR filter, especially in the perspectives of the signal filtering de-noising characteristics and applications. According to the comparison, we can determine which filter is the best.

For many years the analysis of dynamic signals obtained from aero engine mounted transducers has been performed either by using real time spectrum analysers within the test facility, or by making high quality tape recordings during engine tests and analysing the data via an off-line main frame computer. Although real time analysers produce the information where it is most needed, they provide no history of events and the results are operator dependent. Analysis from tape recordings enables information extraction algorithms to be performed and tables and graphs of notable events to be printed. However much of this information could be more effectively utilised if produced within the test facility and in real time. This thesis describes the design and development of a real time data acquisition, signal processing and information extraction system ideally suited for engine health and performance monitoring within test facilities. The thesis begins with a detailed description of the problems encountered in dynamic signal analysis in the field of aero engine performance testing, and with an overview of digital signal processing and the latest technology signal processing micro processors that have made this project possible. It then describes the problems encountered and the subsequent solutions found during the design and development of the hardware and software needed for the·high bandwidth data acquisition and fast signal processing algorithms. The fast Fourier transform has been used for very many years in the field of spectrum analysis, ... however this technique has limitations which are overcome by some of the more modern spectrum estimation techniques. This thesis makes an assessment of some of these techniques, noting particularly their performance on aero engine type signals. The results of these tests are recorded and the possible use of the techniques in aero engine analysis is discussed.

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International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / Pulse Code Modulation (PCM) Encoders are extensively used in instrumentation and telemetry systems. Commercially available encoders are available from several sources and vary in complexity depending on the application. Encoders often include analog signal conditioning, a system clock, and one or more digital input ports. Many of these systems also cost several thousand dollars and the cost goes up when high data accuracy of one or two percent is required. This paper describes a low cost approach which has been used in production telemetry applications with great success and which yields a PCM encoder with data accuracies of better than 2%.