High performance VLSI architecture for Wave Digital Filtering

The application of fine grain pipelining techniques in the design of high performance Wave Digital Filters (WDFs) is described. It is shown that significant increases in the sampling rate of bit parallel circuits can be achieved using most significant bit (msb) first arithmetic. A novel VLSI architecture for implementing two-port adaptor circuits is described which embodies these ideas. The circuit in question is highly regular, uses msb first arithmetic and is implemented using simple carry-save adders. © 1992 Kluwer Academic Publishers.

Bit-Level systolic architectures for high performance IIR filtering

Several novel systolic architectures for implementing densely pipelined bit parallel IIR filter sections are presented. The fundamental problem of latency in the feedback loop is overcome by employing redundant arithmetic in combination with bit-level feedback, allowing a basic first-order section to achieve a wordlength-independent latency of only two clock cycles. This is extended to produce a building block from which higher order sections can be constructed. The architecture is then refined by combining the use of both conventional and redundant arithmetic, resulting in two new structures offering substantial hardware savings over the original design. In contrast to alternative techniques, bit-level pipelinability is achieved with no net cost in hardware. © 1989 Kluwer Academic Publishers.

Pipelined two-port adaptor for wave digital filtering

The application of fine-grain pipelining techniques in the design of high-performance wave digital filters (WDFs) is described. The problems of latency in feedback loops can be significantly reduced if computations are organized most significant, as opposed to least significant, bit first and if the results are fed back as soon as they are formed. The result is that chips can be designed which offer significantly higher sampling rates than otherwise can be obtained using conventional methods. How these concepts can be extended to the more challenging problem of WDFs is discussed. It is shown that significant increases in the sampling rate of bit-parallel circuits can be achieved using most significant bit first arithmetic.

Design methodology for low power and arametric robustness through output-quality modulation:Application to color-interpolation filtering

Power dissipation and robustness to process variation have conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor upsizing for parametric-delay variation tolerance can be detrimental for power dissipation. However, for a class of signal-processing systems, effective tradeoff can be achieved between Vdd scaling, variation tolerance, and output quality. In this paper, we develop a novel low-power variation-tolerant algorithm/architecture for color interpolation that allows a graceful degradation in the peak-signal-to-noise ratio (PSNR) under aggressive voltage scaling as well as extreme process variations. This feature is achieved by exploiting the fact that all computations used in interpolating the pixel values do not equally contribute to PSNR improvement. In the presence of Vdd scaling and process variations, the architecture ensures that only the less important computations are affected by delay failures. We also propose a different sliding-window size than the conventional one to improve interpolation performance by a factor of two with negligible overhead. Simulation results show that, even at a scaled voltage of 77% of nominal value, our design provides reasonable image PSNR with 40% power savings. © 2006 IEEE.

Design methodology to trade off power, output quality and error resiliency: Application to color interpolation filtering

Power dissipation and tolerance to process variations pose conflicting design requirements. Scaling of voltage is associated with larger variations, while Vdd upscaling or transistor up-sizing for process tolerance can be detrimental for power dissipation. However, for certain signal processing systems such as those used in color image processing, we noted that effective trade-offs can be achieved between Vdd scaling, process tolerance and "output quality". In this paper we demonstrate how these tradeoffs can be effectively utilized in the development of novel low-power variation tolerant architectures for color interpolation. The proposed architecture supports a graceful degradation in the PSNR (Peak Signal to Noise Ratio) under aggressive voltage scaling as well as extreme process variations in. sub-70nm technologies. This is achieved by exploiting the fact that some computations are more important and contribute more to the PSNR improvement compared to the others. The computations are mapped to the hardware in such a way that only the less important computations are affected by Vdd-scaling and process variations. Simulation results show that even at a scaled voltage of 60% of nominal Vdd value, our design provides reasonable image PSNR with 69% power savings.

Nonlinear Phase Filtering Effects on GNSS Receiver Positioning Accuracy

This paper demonstrates nonlinear phase filtering effects on GNSS receiver accuracy. Using a nonlinear phase filter in a GNSS receiver can change the pseudorange estimation up to 250 metres which introduces an error in the overall positioning calculation. Paper shows the study of the nonlinear phase filtering effects on the pseudorange estimation and demonstrates how it can be compensated with minimal hardware usage.

Adaptive filtering for high quality HMM based speech synthesis

In this work an adaptive filtering scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for Hidden Markov Model (HMM) based speech synthesis quality enhancement. The objective is to improve signal smoothness across HMMs and their related states and to reduce artifacts due to acoustic model's limitations. Both speech and artifacts are modelled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. Themodel parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The quality enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. The system's performance has been evaluated using mean opinion score tests and the proposed technique has led to improved results.

Median filtering: structure analysis and application

Median filtering is a simple digital non—linear signal smoothing operation in which median of the samples in a sliding window replaces the sample at the middle of the window. The resulting filtered sequence tends to follow polynomial trends in the original sample sequence. Median filter preserves signal edges while filtering out impulses. Due to this property, median filtering is finding applications in many areas of image and speech processing. Though median filtering is simple to realise digitally, its properties are not easily analysed with standard analysis techniques,

Comparison of subspace and ARX models of a waveguide's terahertz transient response after optimal wavelet filtering

A quasi-optical deembedding technique for characterizing waveguides is demonstrated using wide-band time-resolved terahertz spectroscopy. A transfer function representation is adopted for the description of the signal in the input and output port of the waveguides. The time-domain responses were discretized and the waveguide transfer function was obtained through a parametric approach in the z-domain after describing the system with an AutoRegressive with eXogenous input (ARX), as well as with a state-space model. Prior to the identification procedure, filtering was performed in the wavelet domain to minimize both signal distortion, as well as the noise propagating in the ARX and subspace models. The optimal filtering procedure used in the wavelet domain for the recorded time-domain signatures is described in detail. The effect of filtering prior to the identification procedures is elucidated with the aid of pole-zero diagrams. Models derived from measurements of terahertz transients in a precision WR-8 waveguide adjustable short are presented.

Filtering techniques in self-tuning

In the last few years a state-space formulation has been introduced into self-tuning control. This has not only allowed for a wider choice of possible control actions, but has also provided an insight into the theory underlying—and hidden by—that used in the polynomial description. This paper considers many of the self-tuning algorithms, both state-space and polynomial, presently in use, and by starting from first principles develops the observers which are, effectively, used in each case. At any specific time instant the state estimator can be regarded as taking one of two forms. In the first case the most recently available output measurement is excluded, and here an optimal and conditionally stable observer is obtained. In the second case the present output signal is included, and here it is shown that although the observer is once again conditionally stable, it is no longer optimal. This result is of significance, as many of the popular self-tuning controllers lie in the second, rather than first, category.

Human perception-based washout filtering using genetic algorithm

The Motion Cueing Algorithm (MCA) transforms longitudinal and rotational motions into simulator movement, aiming to regenerate high fidelity motion within the simulators physical limitations. Classical washout filters are widely used in commercial simulators because of their relative simplicity and reasonable performance. The main drawback of classical washout filters is the inappropriate empirical parameter tuning method that is based on trial-and-error, and is effected by programmers’ experience. This is the most important obstacle to exploiting the platform efficiently. Consequently, the conservative motion produces false cue motions. Lack of consideration for human perception error is another deficiency of classical washout filters and also there is difficulty in understanding the effect of classical washout filter parameters on generated motion cues. The aim of this study is to present an effortless optimization method for adjusting the classical MCA parameters, based on the Genetic Algorithm (GA) for a vehicle simulator in order to minimize human sensation error between the real and simulator driver while exploiting the platform within its physical limitations. The vestibular sensation error between the real and simulator driver as well as motion limitations have been taken into account during optimization. The proposed optimized MCA based on GA is implemented in MATLAB/Simulink. The results show the superiority of the proposed MCA as it improved the human sensation, maximized reference signal shape following and exploited the platform more efficiently within the motion constraints.

Identification and filtering of uncharacteristic noise in the CMS hadron calorimeter

Commissioning studies of the CMS hadron calorimeter have identified sporadic uncharacteristic noise and a small number of malfunctioning calorimeter channels. Algorithms have been developed to identify and address these problems in the data. The methods have been tested on cosmic ray muon data, calorimeter noise data, and single beam data collected with CMS in 2008. The noise rejection algorithms can be applied to LHC collision data at the trigger level or in the offline analysis. The application of the algorithms at the trigger level is shown to remove 90% of noise events with fake missing transverse energy above 100 GeV, which is sufficient for the CMS physics trigger operation. © 2010 IOP Publishing Ltd and SISSA.

Digital filtering of oscillations intrinsic to transmission line modeling based on lumped parameters

A correction procedure based on digital signal processing theory is proposed to smooth the numeric oscillations in electromagnetic transient simulation results from transmission line modeling based on an equivalent representation by lumped parameters. The proposed improvement to this well-known line representation is carried out with an Finite Impulse Response (FIR) digital filter used to exclude the high-frequency components associated with the spurious numeric oscillations. To prove the efficacy of this correction method, a well-established frequency-dependent line representation using state equations is modeled with an FIR filter included in the model. The results obtained from the state-space model with and without the FIR filtering are compared with the results simulated by a line model based on distributed parameters and inverse transforms. Finally, the line model integrated with the FIR filtering is also tested and validated based on simulations that include nonlinear and time-variable elements. © 2012 Elsevier Ltd. All rights reserved.