Rail-to-rail differential mode input capability in low voltage CMOS transconductor design is implemented by a pull-down and a pull-up follower in an input buffer. By generating three intermediate voltages in the buffe...
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Rail-to-rail differential mode input capability in low voltage CMOS transconductor design is implemented by a pull-down and a pull-up follower in an input buffer. By generating three intermediate voltages in the buffer stage, three voltages are converted to three currents and subsequently summed using MOSFETs operating in the triode region. The nonlinear current components can be cancelled completely. The lowest supply voltage V/sub dd/ is constrained by 2V/sub th/ of the MOS transistors. A single 1.2V operational transconductor amplifier (OTA) was designed using 0.35/spl mu/m CMOS technology and the simulated I-V linearity error is less than 1% within the rail-to-rail differential input range. The achieved THD is less than 0.6% for a 1 KHz, 1.2 V/sub pp/ input signal.
Limited authority of actuators implies that real control signals are always constrained, and in almost all cases, this produces a degradation in the performance of the system. It is thus of practical importance to und...
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Limited authority of actuators implies that real control signals are always constrained, and in almost all cases, this produces a degradation in the performance of the system. It is thus of practical importance to understand the fundamental aspects of this performance degradation. In this paper, we take an initial step by proposing a way to characterize the performance limitations that arise in closed-loop stable linear systems due to the constraints on the magnitude of the control signal. Specifically, we evaluate the cost associated with the constraints via the L 2 norm of the tracking error of a constrained limiting optimal compensator.
A classification scheme is developed for classifying underwater mine-like and non-mine-like objects from acoustic backscattered signals. This scheme uses a predictive network along with a neural network classifier. Th...
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A classification scheme is developed for classifying underwater mine-like and non-mine-like objects from acoustic backscattered signals. This scheme uses a predictive network along with a neural network classifier. The results of this scheme on an acoustic backscattered data set are given.
Thresholdging video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding metho...
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The commonly used linear spectral unmixing is generally performed on a single pixel basis and does not take advantage of inter-pixel spatial correlation. The Kalman filter has been considered to extend the linear unmi...
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ISBN:
(纸本)078037536X
The commonly used linear spectral unmixing is generally performed on a single pixel basis and does not take advantage of inter-pixel spatial correlation. The Kalman filter has been considered to extend the linear unmixing by taking into account both spectral and spatial correlation. In addition to a linear mixture model implemented as a measurement equation, it includes a state equation to keep track of changes in between pixels. However, Kalman filtering requires the complete knowledge of image endmembers present in image data, which is generally not available and very difficult to obtain a priori. In order to relax this dilemma, this paper presents an unsupervised Kalman filtering (UKF) approach to signature estimation for remotely sensed images. It first uses an anomaly detector combined with orthogonal subspace projection (OSP) to extract desired image endmember signatures directly from the image data, then further applies a discrimination measure to classify the extracted signatures into a set of distinct signatures that will be used in the measurement equation. In order for the UKF to effectively capture spatial correlation among sample image pixels, the state equation is also implemented dynamically to adjust the state transition matrix adaptively. Experimental results have shown that the proposed UKF approach provides additional advantages over the commonly used spectral-based linear unmixing methods.
Blood pressure measurement in the finger artery offers some advantages compared with that in the brachial artery. However, volume oscillometric signals obtained from finger artery measurement are often influenced by m...
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Blood pressure measurement in the finger artery offers some advantages compared with that in the brachial artery. However, volume oscillometric signals obtained from finger artery measurement are often influenced by motion artefact due to respiration, speaking, involuntary or voluntary movement, etc. In this paper, we developed a digital envelope detector to detect the maximum oscillation criterion in blood pressure measurement for the first time. The digital envelope detector is robust to noise signals generated by motion artefact and filters out the carrier frequency efficiently. To verify the feasibility of our method, we measured blood pressure for eight subjects using our developed system. The results were compared with the auscultation method. In the case of using a digital envelope detector, we could reduce the mean difference error and standard deviation by 30-40%. Our proposed digital envelope detector is a useful tool to improve the accuracy of blood pressure measurement in finger artery.
Mixed pixel classification is different from spatial-based image classification in the sense that the former deals with abundance fractional images resulting from mixed pixels as opposed to classification maps produce...
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Mixed pixel classification is different from spatial-based image classification in the sense that the former deals with abundance fractional images resulting from mixed pixels as opposed to classification maps produced by the latter. As a result, mixed pixel classification is generally carried out by visual inspection on the generated abundance fractional images. Consequently, it can be very subjective and vary with different human interpretations. Under such circumstance, it is difficult to substantiate an algorithm and conducting a comparative analysis is impossible. This paper presents one histogram-based approach to thresholding abundance fractional images. It thresholds an abundance fractional image into a binary image using a probability of confidence as a threshold value.
Linear-phase lowpass filters are often used as a preprocessing step in signal processing applications to eliminate high frequency components of noise that do not overlap with the signal spectrum. signals with sharp pe...
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Linear-phase lowpass filters are often used as a preprocessing step in signal processing applications to eliminate high frequency components of noise that do not overlap with the signal spectrum. signals with sharp peaks confound this type of noise reduction because sharp peaks have a broad spectrum and are significantly attenuated by lowpass filters. This paper describes a simple method that restores the signal peaks to their full amplitude by adding a filtered estimate of the peak residuals to the original lowpass filter output. Examples are given of the nonlinear filter applied to a Poisson process, an electrocardiogram, and an extracellular microelectrode recording of neuron action potentials.
A relative entropic thresholding approach was recently developed by Chang et al. (see Pattern Recognition, vol. 27, no. 9, p. 1275-1289, 1994). This paper extends Chang et al.'s approach to two more relative entro...
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A relative entropic thresholding approach was recently developed by Chang et al. (see Pattern Recognition, vol. 27, no. 9, p. 1275-1289, 1994). This paper extends Chang et al.'s approach to two more relative entropy-based thresholding methods, called local relative entropy thresholding (LRE) and joint relative entropy thresholding (JRE). Since relative entropy based methods are sensitive to sparse image histograms, a histogram compression and translation is suggested to compact the histogram. In order to achieve an objective assessment, uniformity and shape measures are introduced for performance evaluation. Experimental results show that when image histograms are sparse, with the proposed histogram compression and translation, JRE and LRE generally perform better than Chang et al.'s approach.
Thresholding video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding method...
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Thresholding video images is very challenging due to the fact that image background generally has low resolution and is also more complicated and highly distorted than document images. As a result, thresholding methods that work well for document images may not work effectively for video images in some applications. This paper investigates the issue of thresholding video images for text detection and further develops a relative entropy-based thresholding approach that can effectively extract text from complicated video images. In order to demonstrate its performance a comparative study is conducted among the proposed thresholding method and several thresholding techniques which are widely used for document and gray scale images. The experimental results show that thresholding video images is far more difficult than thresholding document images and simple histogram-based methods generally do not perform well.
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