The design of nearly linear-phase recursive digital filters using constrained optimization is investigated. The design technique proposed is expected to be useful in applications where both magnitude and phase response specifications need to be satisfied. The overall constrained optimization method is formulated as a quadratic programming problem based on Newton’s method. The objective function, its gradient vector and Hessian matrix as well as a set of linear constraints are derived. In this analysis, the independent variables are assumed to be the transfer function coefficients. The filter stability issue and convergence efficiency, as well as a ‘real axis attraction’ problem are solved by integrating the corresponding bounds into the linear constraints of the optimization method. Also, two initialization techniques for providing efficient starting points for the optimization are investigated and the relation between the zero and pole positions and the group delay are examined. Based on these ideas, a new objective function is formulated in terms of the zeros and poles of the transfer function expressed in polar form and integrated into the optimization process. The coefficient-based and polar-based objective functions are tested and compared and it is shown that designs using the polar-based objective function produce improved results. Finally, several other modern methods for the design of nearly linear-phase recursive filters are compared with the proposed method. These include an elliptic design combined with an optimal equalization technique that uses a prescribed group delay, an optimal design method with robust stability using conic-quadratic-programming updates, and an unconstrained optimization technique that uses parameterization to guarantee filter stability. It was found that the proposed method generates similar or improved results in all comparative examples suggesting that the new method is an attractive alternative for linear-phase recursive filters of orders up to about 30.

The design of nearly linear-phase recursive digital filters using constrained optimization is investigated. The design technique proposed is expected to be useful in applications where both magnitude and phase response specifications need to be satisfied. The overall constrained optimization method is formulated as a quadratic programming problem based on Newton’s method. The objective function, its gradient vector and Hessian matrix as well as a set of linear constraints are derived. In this analysis, the independent variables are assumed to be the transfer function coefficients. The filter stability issue and convergence efficiency, as well as a ‘real axis attraction’ problem are solved by integrating the corresponding bounds into the linear constraints of the optimization method. Also, two initialization techniques for providing efficient starting points for the optimization are investigated and the relation between the zero and pole positions and the group delay are examined. Based on these ideas, a new objective function is formulated in terms of the zeros and poles of the transfer function expressed in polar form and integrated into the optimization process. The coefficient-based and polar-based objective functions are tested and compared and it is shown that designs using the polar-based objective function produce improved results. Finally, several other modern methods for the design of nearly linear-phase recursive filters are compared with the proposed method. These include an elliptic design combined with an optimal equalization technique that uses a prescribed group delay, an optimal design method with robust stability using conic-quadratic-programming updates, and an unconstrained optimization technique that uses parameterization to guarantee filter stability. It was found that the proposed method generates similar or improved results in all comparative examples suggesting that the new method is an attractive alternative for linear-phase recursive filters of orders up to about 30.

The overall goal of this work is to provide a systematic methodology by which the difficulties associated with the inverse heat conduction problem (IHCP) can be resolved. To this end, two inverse heat conduction methods are presented. First, a space-marching IHCP method (discrete space, discrete time) utilizing a Gaussian low-pass filter for regularization is studied. The stability and accuracy of this inverse prediction is demonstrated to be more sensitive to the temporal mesh than the spatial mesh. The second inverse heat conduction method presented aims to eliminate this feature by employing a global time, discrete space inverse solution methodology. The novel treatment of the temporal derivative in the heat equation, combined with the global time Gaussian low-pass filter provides the regularization required for stable, accurate results. A physical experiment used as a test bed for validation of the numerical methods described herein is also presented. The physics of installed thermocouple sensors are outlined, and loop-current step response (LCSR) is employed to measure and correct for the delay and attenuation characteristics of the sensors. A new technique for the analysis of LCSR data is presented, and excellent agreement is observed between this model and the data. The space-marching method, global time method, and a new calibration integral method are employed to analyze the experimental data. First, data from only one probe is used which limits the results to the case of a semi-infinite medium. Next, data from two probes at different depths are used in the inverse analysis which enables generalization of the results to domains of finite width. For both one- and two-probe analyses, excellent agreement is found between the actual surface heat flux and the inverse predictions. The most accurate inverse technique is shown to be the calibration integral method, which is presently restricted to one-probe analysis. It is postulated that the accuracy of the global time method could be improved if the required higher-time derivatives of temperature data could be more accurately measured. Some preliminary work in obtaining these higher-time derivatives of temperature from a voltage-rate interface used in conjunction with the thermocouple calibration curve is also presented.

Ett digitalt vågfilter av Richardstyp har implementerats i en FPGA på ett utvecklingskort. Sampel kan skickas till filtret och mottas från filtret via serieporten på en dator. Metoden som användes är att en modell av filtret konstruerades i Simulink. Filtret har modifierats med avseende på skalning, brus och stabilitet. VHDL-koden till filtret genererades i Simulink genom att bygga modellen av Xilinx Blockset. Ytterligare VHDL-kod konstruerades för att kunna skicka sampel mellan filter och minnet på utvecklingskortet. För kommunikation mellan minnet på utvecklingskortet och dator utnyttjades färdiga lösningar. / Filtrets funktion efter implementeringen var samma som modellens byggd i Simulink. A Richards’ structure wave digital filter has been implemented on an evaluation board in an FPGA. Samples can be sent to the filter and received from the filter using the serial port of a computer. The method used is that a modell of the filter has been created in Simulink. The filter has been modified with respect to scaling, noise and stability. VHDL for the filter has been generated in Simulink by using Xilinx blockset to build the modell. Also, VHDL has been constructed to be able to send samples between the filter and the memory on the evaluationboard. For communication between the memory on the evaluationboard and the computer, existing solutions have been used. The functionality of the filter after implementation was the same as in the modell built in Simulink.

This master thesisinvestigates the possibilities to implement a digital filter for wire guidancein a truck. The analog circuits in the truck, today, are analyzed to understandtheir signal processing. The component MAX261 is especially interesting and itis analyzed in a special Section to make sure that all needed details, todevelop a digital filter, are available. When all theoretical calculation wasfinished, all the circuits were simulated to make sure that the calculationsare correct.   The digital filter is based onan analog filter which is expensive and not so easy to purchase. A requirementspecification was developed by analysis of the properties of the analog filterand how it is currently used. The analog filter is a part of a chain of analogsignal processing which mostly can be performed digitally instead.   The special type of the analogfilter makes the requirements, on the digital filter, very tough and anextensive analysis of digital filter structures was performed in order to finda suitable filter. The digital filter is of WDF (Wave Digital Filter)-type andit is very special, because it has two variable coefficients, one for thesteepness and one for the center frequency. The digital filter consists of anumber of first order filters, because a higher order filter with desiredproperties has coefficient values that are large which makes the stabilityproperties worse.   The best type ofimplementation of this filter and the signal processing are also analyzed.Finally, a prototype was developed on a development board where the maincomponent is a DSP (Digital Signal Processor). The program for the prototype iswritten in C-code and the performance of the system was verified by differenttests and measurements.

In different applications, in digital domain, it is necessary to change the sampling rate by an arbitrary number. For example Software Radio which should handle different conversion factors and standards. This work focuses on the problem of designing and implement sampling rate converters for conversions between arbitrary sampling rates. The report presents an overview of different converter techniques as well as considers a suitable scheme with low implementation cost. The creating VHDL generator of Farrow-based structure to speed up the design process is the main task of this work. The suitable design technique which is the most important thing in any design work is presented in the report as well. The scheme which is considered to be suitable is created by VHDL generator and tested in MATLAB. The source code is attached to the report. And some results from tests of the implemented scheme.

The IEEE 802.3aq standard recommends a multi-tap decision feedback equalizer be implemented to remove inter-symbol interference and additive system noise from data transmitted over a 10 Gigabit per Second (10 Gbps) multi-mode fiber-optic link (MMF). The recommended implementation produces a design in an analog process. This design process is difficult, time consuming, and is expensive to modify if first pass silicon success is not achieved. Performing the majority of the design in a well-characterized digital process with stable, evolutionary tools reduces the technical risk. ASIC design rule checking is more predictable than custom tools flows and produces regular, repeatable results. Register Transfer Language (RTL) changes can also be relatively quickly implemented when compared to the custom flow. However, standard cell methodologies are expected to achieve clock rates of roughly one-tenth of the corresponding analog process. The architecture and design for a parallel linear equalizer and decision feedback equalizer are presented. The presented design demonstrates an RTL implementation of 10 GHz filters operating in parallel at 625 MHz. The performance of the filters is characterized by testing the design against a set of 324 reference channels. The results are compared against the IEEE standard group s recommended implementation. The linear equalizer design of 20 taps equalizes 88 % of the reference channels. The decision feedback equalizer design of 20 forward and 1 reverse tap equalizes 93 % of the reference channels. Analysis of the unequalized channels in performed, and areas for continuing research are presented.

Hearing impairment is the number one chronic disability affecting people in the world. Many people have great difficulty in understanding speech with background noise. This is especially true for a large number of elderly people and the sensorineural impaired persons. Several investigations on speech intelligibility have demonstrated that subjects with sensorineural loss may need a 5-15 dB higher signal-to-noise ratio than the normal hearing subjects. While most defects in transmission chain up to cochlea can nowadays be successfully rehabilitated by means of surgery, the great majority of the remaining inoperable cases are sensorineural hearing impaired, Recent statistics of the hearing impaired patients applying for a hearing aid reveal that 20% of the cases are due to conductive losses, more than 50% are due to sensorineural losses, and the rest 30% of the cases are of mixed origin. Presenting speech to the hearing impaired in an intelligible form remains a major challenge in hearing-aid research today. Even-though various methods have been suggested in the literature for the minimization of noise from the contaminated speech signals, they fail to give good SNR improvement and intelligibility improvement for moderate to-severe sensorineural loss subjects. So far, the power and capability of Newton's method, Nonlinear adaptive filtering methods and the feedback type artificial neural networks have not been exploited for this purpose. Hence we resort to the application of all these methods for improving SNR and intelligibility for the sensorineural loss subjects. Digital hearing aids frequently employ the concept of filter banks. One of the major drawbacks of this techniques is the complexity of computation requiring more number of multiplications. This increases the power consumption. Therefore this Thesis presents the new approach to speech enhancement for the hearing impaired and also the construction of filter bank in Digital hearing aid with minimum number of multiplications. The following are covered in this thesis. One of the most important application of adaptive systems is in noise cancellation using adaptive filters. The ANC setup requires two input signals (viz., primary and reference). The primary input consists of the sum of the desired signal and noise which is uncorrelated. The reference input consists of mother noise which is correlated in Some unknown way with noise of primary input. The primary signal is obtained by placing the omnidirectional microphone just above one ear on the head of the KEMAR mannikan and the reference signal is obtained by placing the hypercardioid microphone at the center of the vertebral column on the back. Conventional speech enhancement techniques use linear schemes for enhancing speech signals. So far Nonlinear adaptive filtering techniques are not used in hearing aid applications. The motivation behind the use of nonlinear model is that it gives better noise suppression as compared to linear model. This is because the medium through which signals reach the microphone may be highly nonlinear. Hence the use of linear schemes, though motivated by computational simplicity and mathematical tractability, may be suboptimal. Hence, we propose the use of nonlinear models to enhance the speech signals for the hearing impaired: We propose both Linear LMS and Nonlinear second order Volterra LMS schemes to enhance speech signals. Studies conducted for different environmental noise including babble, cafeteria and low frequency noise show that the second-order Volterra LMS performs better compared to linear LMS algorithm. We use measures such as signal-to-noise ratio (SNR), time plots, and intelligibility tests for performance comparison. We also propose an ANC scheme which uses Newton's method to enhance speech signals. The main problem associated with LMS based ANC is that their convergence is slow and hence their performance becomes poor for hearing aid applications. The reason for choosing Newton's method is that they have high performance adaptive-filtering methods that often converge and track faster than LMS method. We propose two models to enhance speech signals: one is conventional linear model and the other is a nonlinear model using a second order Volterra function. Development of Newton's type algorithm for linear mdel results in familiar Recursive least square (RLS) algorithm. The performance of both linear and non-linear Newton's algorithm is evaluated for babble, cafeteria and frequency noise. SNR, timeplots and intelligibility tests are used for performance comparison. The results show that Newton's method using Volterra nonlinearity performs better than RLS method. ln addition to the ANC based schemes, we also develop speech enhancement for the hearing impaired by using the feedback type neural network (FBNN). The main reason is that here we have parallel algorithm which can be implemented directly in hardware. We translate the speech enhancement problem into a neural network (NN) framework by forming an appropriate energy function. We propose both linear and nonlinear FBNN for enhancing the speech signals. Simulated studies on different environmental noise reveal that the FBNN using the Volterra nonlinearity is superior to linear FBNN in enhancing speech signals. We use SNR, time plots, and intelligibility tests for performance comparison. The design of an effective hearing aid is a challenging problem for sensorineural hearing impaired people. For persons with sensorineural losses it is necessary that the frequency response should be optimally fitted into their residual auditory area. Digital filter enhances the performance of the hearing aids which are either difficult or impossible to realize using analog techniques. The major problem in digital hearing aid is that of reducing power consumption. Multiplication is one of the most power consuming operation in digital filtering. Hence a serious effort has been made to design filter bank with minimum number of multiplications, there by minimizing the power consumption. It is achieved by using Interpolated and complementary FIR filters. This method gives significant savings in the number of arithmetic operations. The Thesis is concluded by summarizing the results of analysis, and suggesting scope for further investigation

<p>This work presents the design and implementation of a decimation filter for a three bits sigma delta analog to digital converter. The input is audio with a oversampling ratio of 32. Filter optimization and tradeoffs concerning the design is described. The filter is a multistage filter consisting of two cascaded FIR filters. The arithmetic unit is a multi-precision unit that can handle three or 24 bits MAC operations. The designed decimation filter is synthesized on standard cells of a 0.13 μm CMOS library.</p>

<p>In different applications, in digital domain, it is necessary to change the sampling rate by an arbitrary number. For example Software Radio which should handle different conversion factors and standards. </p><p>This work focuses on the problem of designing and implement sampling rate converters for conversions between arbitrary sampling rates. </p><p>The report presents an overview of different converter techniques as well as considers a suitable scheme with low implementation cost. The creating VHDL generator of Farrow-based structure to speed up the design process is the main task of this work. The suitable design technique which is the most important thing in any design work is presented in the report as well. </p><p>The scheme which is considered to be suitable is created by VHDL generator and tested in MATLAB. The source code is attached to the report. And some results from tests of the implemented scheme.</p>