The DAP Gamma II is an SIMD computer of either 1024 or 4096 processors (PEs) which can be used as a component in a real-time system. The DAP can be programmed in a mix of high level languages (Fortran-Plus and C++), l...
The DAP Gamma II is an SIMD computer of either 1024 or 4096 processors (PEs) which can be used as a component in a real-time system. The DAP can be programmed in a mix of high level languages (Fortran-Plus and C++), low level languages, and library functions. For easy development of image and signal applications, there is also a development system based on Khoros. Various high-speed I/O interfaces are supported, however the DAP contains a sufficiently large memory to allow sequences of whole-image operations to be performed without any intermediate I/O.
Condition monitoring plays a vital and indispensable role in the operation of any type of plant or machinery. In general, condition monitoring is achieved by processing and interpreting some characteristic signal from...
Condition monitoring plays a vital and indispensable role in the operation of any type of plant or machinery. In general, condition monitoring is achieved by processing and interpreting some characteristic signal from the plant under consideration. Traditionally, only linear second order statistical analysis has been used to process the characteristic signals from plant, however, a new approach to condition monitoring called higher order statistics is becoming increasingly prevalent. A small body of research has been concentrated on using higher order statistical techniques within a condition monitoring environment but the success of this work has been hampered by the lack of generality of the technique. This submission investigates a method of capitalising on the attractive properties of such techniques in an intelligent and simple fashion in the construction of a comprehensive, generalised condition monitoring tool. This is demonstrated by practical investigation of the condition monitoring of an induction machine.
Insight into the core of the pipelined recurrent neural network (PRNN) in prediction applications is provided. It is shown that modules of the PRNN contribute to the final predicted value at the output of the PRNN in ...
Insight into the core of the pipelined recurrent neural network (PRNN) in prediction applications is provided. It is shown that modules of the PRNN contribute to the final predicted value at the output of the PRNN in two ways, namely through the process of nesting, and through the process of learning. A measure of the influence of the output of a distant module to the amplitude at the output of the PRNN is analytically found, and the upper bound for it is derived. Furthermore, an analysis of the influence of the forgetting factor in the cost function of the PRNN to the process of learning is undertaken, and it is found that for the PRNN, the forgetting factor can even exceed unity in order to obtain the best predictor. Simulations on three speech signals support that approach, and outperform the other stochastic gradient based schemes.
Median filters are probably the most widely used of the noise suppression filters that are commonly applied to digital images. They are vastly superior to mean filters since the latter are well known to blur images as...
Median filters are probably the most widely used of the noise suppression filters that are commonly applied to digital images. They are vastly superior to mean filters since the latter are well known to blur images as well as removing noise. Median filters do not suffer from this disadvantage. Although median filters do not blur images, it has been found that they can cause a certain amount of image distortion by shifting edges (Davies 1997). This paper reviews previous work on the computation of shifts produced by mean, median and mode filters using continuum models. The paper proceeds to show how, in the case of median filters, it can be extended using discrete models to give more accurate predictions that are in line with experimental measurements.
Ultrasound pulses propagating through human tissue appear to retain most of their initial coherence, and are coherently scattered from the many inhomogeneities within a tissue. A complex echo field is generated which ...
Ultrasound pulses propagating through human tissue appear to retain most of their initial coherence, and are coherently scattered from the many inhomogeneities within a tissue. A complex echo field is generated which exhibits many interference effects, the most familiar of these manifests itself as the ubiquitous speckle artefact. Speckle pervades almost all medical ultrasound pulse-echo signals and imposes a fundamental limit on signal and image quality. It is commonly assumed that the removal of speckle will produce a great advantage in a large number of practical applications. The novel approach developed here provides a general descriptive framework for interference effects, and is based on a description of interference by the presence of what we have termed structure zeros in the analytic continuation of the real data into the complex frequency, and complex time domains. The structure zeros may be uniquely identified if the form of the interrogating ultrasound pulse is precisely known. In practice, the latter requirement cannot be satisfied, and the presence of noise introduces a further element of uncertainty, but the structure zeros which make the dominant contribution to signal corruption may be unambiguously identified (via a sensitivity index) when short data segments are considered. Appropriate manipulation of the structure zero locations results in a specific, desired correction to the signal.
There are an increasing number of applications of automated image analysis in which imaging is part of an instrumentation or process control system. A variety of industrial processes, including quality control and ass...
There are an increasing number of applications of automated image analysis in which imaging is part of an instrumentation or process control system. A variety of industrial processes, including quality control and assembly, robotic, security and other applications make use of machine vision. Such embedded applications often require performance to be tuned in various ways to satisfy time constraints, which may vary through the lifetime of the application. There may, in addition, be a requirement to produce versions of an imaging product targetted at different classes of user, to satisfy various market niches, for example. It is therefore important to develop software tools which allow developers to relatively easily target a variety of computational engines. Possible target systems may include PC, dedicated microprocessor or digital signal processor, multiprocessors, or custom hardware. We report our experience in applying hardware compilation technology in an FPGA-based system to some typical imageprocessing tasks.
In the field of medical signal and imageprocessing the usual uncertainties in our knowledge are often compounded by a poor understanding of the physical mechanisms by which the data is generated and a subjective eval...
In the field of medical signal and imageprocessing the usual uncertainties in our knowledge are often compounded by a poor understanding of the physical mechanisms by which the data is generated and a subjective evaluation of the data by a human observer. In the case of the EEG, the effects of scalp, fluid and bone on the tiny electrical currents generated in the cortex may be modelled only poorly and the large size of scalp electrodes and the effects of muscle and instrument noise all contribute to the difficulty of EEG analysis. The belief that the EEG contains some objective information regarding brain state is tantalising. We do not discuss in detail the problems of noise and artifact removal, nor the problems of modelling the passage of the EEG from cortex to scalp, but instead concentrate on the EEG as is and suggest that, even if such problems are not solved, the EEG contains significant objective information regarding cortical functioning. We focus upon two main areas of information processing, namely information extraction from an EEG record (feature extraction and representation) and pattern recognition and inference.
The proceedings contains 9 papers on the use of model based digital signalprocessing techniques in the analysis of biomedical signals. Topics discussed include: digital signalprocessing;deterministic modelling;param...
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The proceedings contains 9 papers on the use of model based digital signalprocessing techniques in the analysis of biomedical signals. Topics discussed include: digital signalprocessing;deterministic modelling;parametric model order estimation;cardiovascular variability;respiratory impedance;foetal electrocardiography separation;electrical impedance tomography;and image reconstruction.
The data being analyzed were obtained from an electrical impedance tomography (EIT) comprising 32 independently programmable current sources and 32 voltage measurement channels attached respectively to separate electr...
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The data being analyzed were obtained from an electrical impedance tomography (EIT) comprising 32 independently programmable current sources and 32 voltage measurement channels attached respectively to separate electrodes around the chest of a male volunteer. The 64 (ECG) electrodes separate were equally spaced on the skin in a sagittal plane approximately 2 cms. below the level of the nipples. The reconstruction problem for EIT is non-linear and highly ill-posed.
Many intensive and real-time signalprocessing applications for example in control, speech synthesis/recognition and imageprocessing, have computational requirements which are too high for implementation on single DS...
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Many intensive and real-time signalprocessing applications for example in control, speech synthesis/recognition and imageprocessing, have computational requirements which are too high for implementation on single DSP processors. Parallel implementation on multiple DSP processors provides an attractive solution to this problem. This paper presents a code generator which is capable of automatically producing parallel code for a multiprocessor hardware platform. The generator makes use of special code skeletons to abstract away from the hardware platform being used, and hence providing a high degree of flexibility in the choice of platforms. By using a consistent interface to these skeletons one can easily retarget the same signalprocessing application to different hardware systems. The design philosophy and architecture of the code generator as well as the types of multiprocessor hardware platforms used are presented and discussed.
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