FRM-Based FIR filters with minimum coefficient sensitivities

A method for optimizing FRM-based FIR filters with optimum coefficient sensitivity is presented. This technique can be used in conjunction with nonlinear optimization techniques to design very sharp filters that do not only have very sparse coefficient values but also very low coefficient sensitivity

Multirate digital filters, filter banks, polyphase networks, and applications: a tutorial

Multirate digital filters and filter banks find application in communications, speech processing, image compression, antenna systems, analog voice privacy systems, and in the digital audio industry. During the last several years there has been substantial progress in multirate system research. This includes design of decimation and interpolation filters, analysis/synthesis filter banks (also called quadrature mirror filters, or QMFJ, and the development of new sampling theorems. First, the basic concepts and building blocks in multirate digital signal processing (DSPJ, including the digital polyphase representation, are reviewed. Next, recent progress as reported by several authors in this area is discussed. Several applications are described, including the following: subband coding of waveforms, voice privacy systems, integral and fractional sampling rate conversion (such as in digital audio), digital crossover networks, and multirate coding of narrow-band filter coefficients. The M-band QMF bank is discussed in considerable detail, including an analysis of various errors and imperfections. Recent techniques for perfect signal reconstruction in such systems are reviewed. The connection between QMF banks and other related topics, such as block digital filtering and periodically time-varying systems, based on a pseudo-circulant matrix framework, is covered. Unconventional applications of the polyphase concept are discussed

Studies on Implementation of . . . High Throughput and Low Power Consumption

In this thesis we discuss design and implementation of frequency selective digital filters with high throughput and low power consumption. The thesis includes proposed arithmetic transformations of lattice wave digital filters that aim at increasing the throughput and reduce the power consumption of the filter implementation. The thesis also includes two case studies where digital filters with high throughput and low power consumption are required. A method for obtaining high throughput as well as reduced power consumption of digital filters is arithmetic transformation of the filter structure. In this thesis arithmetic transformations of first- and second-order Richards’ allpass sections composed by symmetric two-port adaptors and implemented using carry-save arithmetic are proposed. Such filter sections can be used for implementation of lattice wave digital filters and bireciprocal lattice wave digital filters. The latter structures are efficient for implementation of interpolators and decimators by factors of two. Th

Channelization for Multi-Standard Software-Defined Radio Base Stations

As the number of radio standards increase and spectrum resources come under more pressure, it becomes ever less efficient to reserve bands of spectrum for exclusive use by a single radio standard. Therefore, this work focuses on channelization structures compatible with spectrum sharing among multiple wireless standards and dynamic spectrum allocation in particular. A channelizer extracts independent communication channels from a wideband signal, and is one of the most computationally expensive components in a communications receiver. This work specifically focuses on non-uniform channelizers suitable for multi-standard Software-Defined Radio (SDR) base stations in general and public mobile radio base stations in particular. A comprehensive evaluation of non-uniform channelizers (existing and developed during the course of this work) shows that parallel and recombined variants of the Generalised Discrete Fourier Transform Modulated Filter Bank (GDFT-FB) represent the best trade-off between computational load and flexibility for dynamic spectrum allocation. Nevertheless, for base station applications (with many channels) very high filter orders may be required, making the channelizers difficult to physically implement. To mitigate this problem, multi-stage filtering techniques are applied to the GDFT-FB. It is shown that these multi-stage designs can significantly reduce the filter orders and number of operations required by the GDFT-FB. An alternative approach, applying frequency response masking techniques to the GDFT-FB prototype filter design, leads to even bigger reductions in the number of coefficients, but computational load is only reduced for oversampled configurations and then not as much as for the multi-stage designs. Both techniques render the implementation of GDFT-FB based non-uniform channelizers more practical. Finally, channelization solutions for some real-world spectrum sharing use cases are developed before some final physical implementation issues are considered

Digital Filters

The new technology advances provide that a great number of system signals can be easily measured with a low cost. The main problem is that usually only a fraction of the signal is useful for different purposes, for example maintenance, DVD-recorders, computers, electric/electronic circuits, econometric, optimization, etc. Digital filters are the most versatile, practical and effective methods for extracting the information necessary from the signal. They can be dynamic, so they can be automatically or manually adjusted to the external and internal conditions. Presented in this book are the most advanced digital filters including different case studies and the most relevant literature

Efficient Multiband Algorithms for Blind Source Separation

The problem of blind separation refers to recovering original signals, called source signals, from the mixed signals, called observation signals, in a reverberant environment. The mixture is a function of a sequence of original speech signals mixed in a reverberant room. The objective is to separate mixed signals to obtain the original signals without degradation and without prior information of the features of the sources. The strategy used to achieve this objective is to use multiple bands that work at a lower rate, have less computational cost and a quicker convergence than the conventional scheme. Our motivation is the competitive results of unequal-passbands scheme applications, in terms of the convergence speed. The objective of this research is to improve unequal-passbands schemes by improving the speed of convergence and reducing the computational cost. The first proposed work is a novel maximally decimated unequal-passbands scheme.This scheme uses multiple bands that make it work at a reduced sampling rate, and low computational cost. An adaptation approach is derived with an adaptation step that improved the convergence speed. The performance of the proposed scheme was measured in different ways. First, the mean square errors of various bands are measured and the results are compared to a maximally decimated equal-passbands scheme, which is currently the best performing method. The results show that the proposed scheme has a faster convergence rate than the maximally decimated equal-passbands scheme. Second, when the scheme is tested for white and coloured inputs using a low number of bands, it does not yield good results; but when the number of bands is increased, the speed of convergence is enhanced. Third, the scheme is tested for quick changes. It is shown that the performance of the proposed scheme is similar to that of the equal-passbands scheme. Fourth, the scheme is also tested in a stationary state. The experimental results confirm the theoretical work. For more challenging scenarios, an unequal-passbands scheme with over-sampled decimation is proposed; the greater number of bands, the more efficient the separation. The results are compared to the currently best performing method. Second, an experimental comparison is made between the proposed multiband scheme and the conventional scheme. The results show that the convergence speed and the signal-to-interference ratio of the proposed scheme are higher than that of the conventional scheme, and the computation cost is lower than that of the conventional scheme

Design and implementation of computationally efficient digital filters

Ph.DDOCTOR OF PHILOSOPH

NONUNIFORMLY SAMPLED DIGITAL SIGNAL PROCESSING FOR LOW-POWER BIOMEDICAL APPLICATIONS.

Ph.DDOCTOR OF PHILOSOPH

Picture coding in viewdata systems

Viewdata systems in commercial use at present offer the facility for transmitting alphanumeric text and graphic displays via the public switched telephone network. An enhancement to the system would be to transmit true video images instead of graphics. Such a system, under development in Britain at present uses Differential Pulse Code Modulation (DPCM) and a transmission rate of 1200 bits/sec. Error protection is achieved by the use of error protection codes, which increases the channel requirement. In this thesis, error detection and correction of DPCM coded video signals without the use of channel error protection is studied. The scheme operates entirely at the receiver by examining the local statistics of the received data to determine the presence of errors. Error correction is then undertaken by interpolation from adjacent correct or previousiy corrected data. DPCM coding of pictures has the inherent disadvantage of a slow build-up of the displayed picture at the receiver and difficulties with image size manipulation. In order to fit the pictorial information into a viewdata page, its size has to be reduced. Unitary transforms, typically the discrete Fourier transform (DFT), the discrete cosine transform (DCT) and the Hadamard transform (HT) enable lowpass filtering and decimation to be carried out in a single operation in the transform domain. Size reductions of different orders are considered and the merits of the DFT, DCT and HT are investigated. With limited channel capacity, it is desirable to remove the redundancy present in the source picture in order to reduce the bit rate. Orthogonal transformation decorrelates the spatial sample distribution and packs most of the image energy in the low order coefficients. This property is exploited in bit-reduction schemes which are adaptive to the local statistics of the different source pictures used. In some cases, bit rates of less than 1.0 bit/pel are achieved with satisfactory received picture quality. Unlike DPCM systems, transform coding has the advantage of being able to display rapidly a picture of low resolution by initial inverse transformation of the low order coefficients only. Picture resolution is then progressively built up as more coefficients are received and decoded. Different sequences of picture update are investigated to find that which achieves the best subjective quality with the fewest possible coefficients transmitted