An FPGA architecture design of a high performance adaptive notch filter

The occurrence of narrowband interference near frequencies carrying information is a common problem in modern control and signal processing applications. A very narrow notch filter is required in order to remove the unwanted signal while not compromising the integrity of the carrier signal. In many practical situations, the interference may wander within a frequency band, in which case a wider notch filter would be needed to guarantee its removal, which may also allow for the degradation of information being carried in nearby frequencies. If the interference frequency could be autonomously tracked, a narrow bandwidth notch filter could be successfully implemented for the particular frequency. Adaptive signal processing is a powerful technique that can be used in the tracking and elimination of such a signal. An application where an adaptive notch filter becomes necessary is in biomedical instrumentation, such as the electrocardiogram recorder. The recordings can become useless when in the presence of electromagnetic fields generated by power lines. Research was conducted to fully characterize the interference. Research on notch filter structures and adaptive filter algorithms has been carried out. The lattice form filter structure was chosen for its inherent stability and performance benefits. A new adaptive filter algorithm was developed targeting a hardware implementation. The algorithm used techniques from several other algorithms that were found to be beneficial. This work developed the hardware implementation of a lattice form adaptive notch filter to be used for the removal of power line interference from electrocardiogram signals. The various design tradeo s encountered were documented. The final design was targeted toward multiple field programmable gate arrays using multiple optimization efforts. Those results were then compared. The adaptive notch filter was able to successfully track and remove the interfering signal. The lattice form structure utilized by the proposed filter was verified to exhibit an inherently stable realization. The filter was subjected to various environments that modeled the different power line disturbances that could be present. The final filter design resulted in a 3 dB bandwidth of 15.8908 Hz, and a null depth of 54 dB. For the baseline test case, the algorithm achieved convergence after 270 iterations. The final hardware implementation was successfully verified against the MATLAB simulation results. A speedup of 3.8 was seen between the Xilinx Virtex-5 and Spartan-II device technologies. The final design used a small fraction of the available resources for each of the two devices that were characterized. This would allow the component to be more readily available to be added to existing projects, or further optimized by utilizing additional logic

Generalized linear-in-parameter models : theory and audio signal processing applications

This thesis presents a mathematically oriented perspective to some basic concepts of digital signal processing. A general framework for the development of alternative signal and system representations is attained by defining a generalized linear-in-parameter model (GLM) configuration. The GLM provides a direct view into the origins of many familiar methods in signal processing, implying a variety of generalizations, and it serves as a natural introduction to rational orthonormal model structures. In particular, the conventional division between finite impulse response (FIR) and infinite impulse response (IIR) filtering methods is reconsidered. The latter part of the thesis consists of audio oriented case studies, including loudspeaker equalization, musical instrument body modeling, and room response modeling. The proposed collection of IIR filter design techniques is submitted to challenging modeling tasks. The most important practical contribution of this thesis is the introduction of a procedure for the optimization of rational orthonormal filter structures, called the BU-method. More generally, the BU-method and its variants, including the (complex) warped extension, the (C)WBU-method, can be consider as entirely new IIR filter design strategies.reviewe

Adaptive IIR filtering using the homotopy continuation method

The objective of this study is to develop an algorithmic approach for solving problems associated with the convergence to the local minima in adaptive IIR filtering. The approach is based on a numerical method called the homotopy continuation method;The homotopy continuation method is a solution exhaustive method for calculating all solutions of a set of nonlinear equations. The globally optimum filter coefficients correspond to the solutions with minimum mean square error. In order to apply the technique to the adaptive IIR filtering problem, the homotopy continuation method is modified to handle a set of nonlinear polynomials with time-varying coefficients. Then, the adaptive IIR filtering problem is formulated in terms of a set of nonlinear polynomials using the mean square output error minimization approach. The adaptive homotopy continuation method (AHCM) for the case of time-varying coefficients is then applied to solve the IIR filtering problem. After demonstrating the feasibility of the approach, problems encountered in the basic AHCM algorithm are discussed and alternative structures of the filter are proposed. In the development of the proposed algorithm and its variations, the instability problem which is a second disadvantage of IIR filters is also considered;Simulation results for a system identification example validate the proposed algorithm by determining the filter coefficients at the global minimum position. For further validation, the AHCM algorithm is then applied to an adaptive noise cancellation application in ultrasonic nondestructive evaluation. Ultrasonic inspection signal reflections from defects and material grain boundaries are considered. The AHCM algorithm is applied to the noise cancellation mode to filter out the material noise. The experimental results show that the proposed algorithm shows considerable promise for real as well as for simulated data

Real-Time Quantum Noise Suppression In Very Low-Dose Fluoroscopy

Fluoroscopy provides real-time X-ray screening of patient's organs and of various radiopaque objects, which make it an invaluable tool for many interventional procedures. For this reason, the number of fluoroscopy screenings has experienced a consistent growth in the last decades. However, this trend has raised many concerns about the increase in X-ray exposure, as even low-dose procedures turned out to be not as safe as they were considered, thus demanding a rigorous monitoring of the X-ray dose delivered to the patients and to the exposed medical staff. In this context, the use of very low-dose protocols would be extremely beneficial. Nonetheless, this would result in very noisy images, which need to be suitably denoised in real-time to support interventional procedures. Simple smoothing filters tend to produce blurring effects that undermines the visibility of object boundaries, which is essential for the human eye to understand the imaged scene. Therefore, some denoising strategies embed noise statistics-based criteria to improve their denoising performances. This dissertation focuses on the Noise Variance Conditioned Average (NVCA) algorithm, which takes advantage of the a priori knowledge of quantum noise statistics to perform noise reduction while preserving the edges and has already outperformed many state-of-the-art methods in the denoising of images corrupted by quantum noise, while also being suitable for real-time hardware implementation. Different issues are addressed that currently limit the actual use of very low-dose protocols in clinical practice, e.g. the evaluation of actual performances of denoising algorithms in very low-dose conditions, the optimization of tuning parameters to obtain the best denoising performances, the design of an index to properly measure the quality of X-ray images, and the assessment of an a priori noise characterization approach to account for time-varying noise statistics due to changes of X-ray tube settings. An improved NVCA algorithm is also presented, along with its real-time hardware implementation on a Field Programmable Gate Array (FPGA). The novel algorithm provides more efficient noise reduction performances also for low-contrast moving objects, thus relaxing the trade-off between noise reduction and edge preservation, while providing a further reduction of hardware complexity, which allows for low usage of logic resources also on small FPGA platforms. The results presented in this dissertation provide the means for future studies aimed at embedding the NVCA algorithm in commercial fluoroscopic devices to accomplish real-time denoising of very low-dose X-ray images, which would foster their actual use in clinical practice

Channel Equalization using GA Family

High speed data transmissions over communication channels distort the trans- mitted signals in both amplitude and phase due to presence of Inter Symbol Inter- ference (ISI). Other impairments like thermal noise, impulse noise and cross talk also cause further distortions to the received symbols. Adaptive equalization of the digital channels at the receiver removes/reduces the e®ects of such ISIs and attempts to recover the transmitted symbols. Basically an equalizer is an inverse ¯lter which is placed at the front end of the receiver. Its transfer function is inverse to the transfer function of the associated channel. The Least-Mean-Square (LMS), Recursive-Least-Square (RLS) and Multilayer perceptron (MLP) based adaptive equalizers aim to minimize the ISI present in the digital communication channel. These are gradient based learning algorithms and therefore there is possibility that during training of the equalizers, its weights do not reach to their optimum values due to ..

Adaptive Channel Equalization using Radial Basis Function Networks and MLP

One of the major practical problems in digital communication systems is channel distortion which causes errors due to intersymbol interference. Since the source signal is in general broadband, the various frequency components experience different steady state amplitude and phase changes as they pass through the channel, causing distortion in the received message. This distortion translates into errors in the received sequence. Our problem as communication engineers is to restore the transmitted sequence or, equivalently, to identify the inverse of the channel, given the observed sequence at the channel output. This task is accomplished by adaptive equalizers. Typically, adaptive equalizers used in digital communications require an initial training period, during which a known data sequence is transmitted. A replica of this sequence is made available at the receiver in proper synchronism with the transmitter, thereby making it possible for adjustments to be made to the equalizer coefficients in accordance with the adaptive filtering algorithm employed in the equalizer design. When the training is completed, the equalizer is switched to its decision directed mode. Decision feedback equalizers are used extensively in practical communication systems. They are more powerful than linear equalizers especially for severe inter-symbol interference (ISI) channels without as much noise enhancement as the linear equalizers. This thesis addresses the problem of adaptive channel equalization in environments where the interfering noise exhibits Gaussian behavior. In this thesis, radial basis function (RBF) network is used to implement DFE. Advantages and problems of this system are discussed and its results are then compared with DFE using multi layer perceptron net (MLP).Results indicate that the implemented system outperforms both the least-mean square(LMS) algorithm and MLP, given the same signal-to-noise ratio as it offers minimum mean square error. The learning rate of the implemented system is also faster than both LMS and the multilayered case

Digital signal processing algorithms and structures for adaptive line enhancing

Imperial Users onl

Techniques to Improve the Efficiency of Data Transmission in Cable Networks

The cable television (CATV) networks, since their introduction in the late 1940s, have now become a crucial part of the broadcasting industry. To keep up with growing demands from the subscribers, cable networks nowadays not only provide television programs but also deliver two-way interactive services such as telephone, high-speed Internet and social TV features. A new standard for CATV networks is released every five to six years to satisfy the growing demands from the mass market. From this perspective, this thesis is concerned with three main aspects for the continuing development of cable networks: (i) efficient implementations of backward-compatibility functions from the old standard, (ii) addressing and providing solutions for technically-challenging issues in the current standard and, (iii) looking for prospective features that can be implemented in the future standard. Since 1997, five different versions of the digital CATV standard had been released in North America. A new standard often contains major improvements over the previous one. The latest version of the standard, namely DOCSIS 3.1 (released in late 2013), is packed with state-of-the-art technologies and allows approximately ten times the amount of traffic as compared to the previous standard, DOCSIS 3.0 (released in 2008). Backward-compatibility is a must-have function for cable networks. In particular, to facilitate the system migration from older standards to a newer one, the backward compatible functions in the old standards must remain in the newer-standard products. More importantly, to keep the implementation cost low, the inherited backward compatible functions must be redesigned by taking advantage of the latest technology and algorithms. To improve the backward-compatibility functions, the first contribution of the thesis focuses on redesigning the pulse shaping filter by exploiting infinite impulse response (IIR) filter structures as an alternative to the conventional finite impulse response (FIR) structures. Comprehensive comparisons show that more economical filters with better performance can be obtained by the proposed design algorithm, which considers a hybrid parameterization of the filter's transfer function in combination with a constraint on the pole radius to be less than 1. The second contribution of the thesis is a new fractional timing estimation algorithm based on peak detection by log-domain interpolation. When compared with the commonly-used timing detection method, which is based on parabolic interpolation, the proposed algorithm yields more accurate estimation with a comparable implementation cost. The third contribution of the thesis is a technique to estimate the multipath channel for DOCSIS 3.1 cable networks. DOCSIS 3.1 is markedly different from prior generations of CATV networks in that OFDM/OFDMA is employed to create a spectrally-efficient signal. In order to effectively demodulate such a signal, it is necessary to employ a demodulation circuit which involves estimation and tracking of the multipath channel. The estimation and tracking must be highly accurate because extremely dense constellations such as 4096-QAM and possibly 16384-QAM can be used in DOCSIS 3.1. The conventional OFDM channel estimators available in the literature either do not perform satisfactorily or are not suitable for the DOCSIS 3.1 channel. The novel channel estimation technique proposed in this thesis iteratively searches for parameters of the channel paths. The proposed technique not only substantially enhances the channel estimation accuracy, but also can, at no cost, accurately identify the delay of each echo in the system. The echo delay information is valuable for proactive maintenance of the network. The fourth contribution of this thesis is a novel scheme that allows OFDM transmission without the use of a cyclic prefix (CP). The structure of OFDM in the current DOCSIS 3.1 does not achieve the maximum throughput if the channel has multipath components. The multipath channel causes inter-symbol-interference (ISI), which is commonly mitigated by employing CP. The CP acts as a guard interval that, while successfully protecting the signal from ISI, reduces the transmission throughput. The problem becomes more severe for downstream direction, where the throughput of the entire system is determined by the user with the worst channel. To solve the problem, this thesis proposes major alterations to the current DOCSIS 3.1 OFDM/OFDMA structure. The alterations involve using a pair of Nyquist filters at the transceivers and an efficient time-domain equalizer (TEQ) at the receiver to reduce ISI down to a negligible level without the need of CP. Simulation results demonstrate that, by incorporating the proposed alterations to the DOCSIS 3.1 down-link channel, the system can achieve the maximum throughput over a wide range of multipath channel conditions

High bit-rate digital communication through metal channels

The need to transmit digital information across metallic barriers arises frequently in industrial control applications. In some applications, the barrier can be penetrated with wiring, while in others this may not be possible. For example, metal bulkheads, pressure vessels, or pipelines may require a level of mechanical integrity that prohibits mechanical penetration. This study investigates the use of ultrasonic signaling for data transmission across metallic barriers, discusses the associated challenges, and analyzes several alternative communication system implementations.Several recent e orts have been made to develop through-metal ultrasonic communication systems, with approaches ranging widely in bitrate, complexity, and power requirements. The transceiver designs presented here are intended to cover a range of target applications. In systems having low data rate requirements, simple transceivers with low hardware/software complexity can be used. At high data rates, however, severe echoing in the ultrasonic channel leads to intersymbol interference. Reliable high speed communication therefore requires the use of channel equalizers, and results in a transceiver with higher hardware/software complexity.In this thesis, issues related to the design of reliable through-metal ultrasonic communication systems are discussed. These include (1) the development of mathematical models used to characterize the channel, (2) application of equalization techniques needed to achieve high-speed communication, and (3) analysis of hardware/software complexity for alternative transceiver designs.Several groups have developed through-metal ultrasonic communication systems in the recent past, though none has produced a mathematical model that accurately describes the phenomena found within the channel. The channel model developed in this thesis can be used at several stages of the transceiver design process, from transducer selection through channel equalizer design and ultimately system performance simulation.Using this channel model, we go on to develop and test several ultrasonic throughmetal transceiver designs. Ultrasonic through-metal communication systems are finding use in a wide variety of applications. Some require high throughput, while others require low power consumption. The motivation for developing several designs { ranging from low complexity, low power to high complexity, high throughput { is so that the best design can be matched to each application.After these transceiver designs are developed, we present an analysis of their computational requirements so that the most appropriate transceiver can be chosen for a given application.Ph.D., Electrical Engineering -- Drexel University, 201