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The backplane environment presents a serious challenge to sig-naling rates above 5Gb/s. Previous 10Gb/s transceivers [1] are not designed for this harsh environment. In the raw single bit response of Fig. 4.6.1, a single 200ps pulse undergoes serious loss and dispersion and initiates reflections that may be a significant percentage of an equalized eye.(More)
Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Here, we use the term space-varying convolution to refer to linear operators whose impulse response has slow spatial variation. In addition, these space-varying convolution operators are often dense, so direct(More)
OBJECTIVE Epiretinal prostheses are designed to restore functional vision to the blind by electrically stimulating surviving retinal neurons. These devices have classically employed symmetric biphasic current pulses in order to maintain a balance of charge. Prior electrophysiological and psychophysical studies in peripheral nerve show that adding an(More)
Space-varying convolution often arises in the modeling or restoration of images captured by optical imaging systems. For example, in applications such as microscopy or photography the distortions introduced by lenses typically vary across the field of view, so accurate restoration also requires the use of space-varying convolu-tion. While space-invariant(More)
—Many imaging applications require the implementation of space-varying convolution for accurate restoration and reconstruction of images. Moreover, these space-varying convo-lution operators are often dense, so direct implementation of the convolution operator is typically computationally impractical. One such example is the problem of stray light reduction(More)
We propose a new model for event-related functional magnetic resonance imaging (fMRI), and develop a new set of tools for activation detection. A novel feature of our framework is the explicit modeling of the spatial correlation introduced by the scanner. We propose simple, efficient algorithms to estimate model parameters. We develop an activation(More)
We employ our previously proposed framework [18] for the analysis of event-related functional magnetic resonance imaging (fMRI) data. In [18], we use a Gaussian blurring kernel to explicitly model the spatial correlation introduced by the scanner. In the present paper, we propose an improved strategy for estimating the extent of this spatial blurring. We(More)