A new class of filter transfer function derived from Wiener filter and Green’s equivalent layer principles is presented for upward and downward‐continuation enhancement of potential‐field data. The newly developed transfer function is called the preferential continuation operator. In contrast to the conventional continuation operator, the preferential continuation operator possesses a continuation response that acts preferentially upon a specific band of the observed potential field’s Fourier amplitude spectrum. The transfer function response approaches the response of an all‐pass filter away from this band. This response characteristic is useful for at least two common potential‐field signal enhancement applications. First, it is possible with preferential upward continuation to attenuate shallow‐source, short‐wavelength, potential‐field signals while minimally attenuating deep‐source, long wavelength signals (as often happens after application of conventional upward continuation) Second, it is possible with preferential downward continuation to enhance deep‐source, long wavelength signals without overamplifying shallow‐source, short‐wavelength signals (as often happens after application of conventional downward continuation) Preferential continuation, used qualitatively for anomaly enhancement, ably overcomes these two limitations of conventional continuation enhancement.

Using simple estimates of the signal and noise power from gridded magnetic data, we design regulated frequency‐domain operators for reduction to the pole at low magnetic latitudes. These operators suppress the artifacts along the direction of the magnetic declination associated with the conventional reduction‐to‐the‐pole procedure, with negligible increase in computational load. The new procedure is applied to produce high‐quality reductions to the pole for noisy low‐latitude synthetic data and for magnetic data from the Dixon Seamount.

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We introduce a gravity anomaly separation method based on frequency‐domain Wiener filtering. Gravity anomaly separation can be effected by such wavelength filtering when the gravity response from the geologic feature of interest (the signal) dominates one region (or spectral band) of the observed gravity field’s power spectrum. The Wiener filter is preferable to a conventional band‐pass filter because geologic information from the study area can be incorporated to a greater extent in specifying the filter’s transfer function. Our method differs from previous Wiener filtering schemes in that it provides, through direct modeling of known geology (e.g., outcrop and borehole data), a more objective estimate of the signal power spectrum required for defining the transfer function of the filter. We illustrate the technique first with synthetic data, and then with a field example from the southern Paradox basin. The Paradox basin example reveals the limitation inherent to all wavelength filtering which results from spectral overlap between the gravity signal and the spectral contributions of other geologic sources. In the study area, significant spectral overlap occurs between the gravity effects of sources in the Precambrian basement and the gravity signal arising from the density contrast across the Mississippian‐Pennsylvanian interface.

Abstract-While Moore's law scaling continues to double transistor density every technology generation, supply voltage reduction has essentially stopped, increasing both power density and total energy consumed in conventional microprocessors. Therefore, future processors will require an architecture that can: a) take advantage of the massive amount of transistors that will be available; and b) operate these transistors in the near-threshold supply domain, thereby achieving near optimal energy/computation by balancing the leakage and dynamic energy consumption. Unfortunately, this optimality is typically achieved while running at very low frequencies (i.e. 0.1 − 10MHz ) and with only one computation executing per cycle, such that performance is limited. Further, near-threshold designs suffer from severe process variability that can introduce extremely large delay variations. In this paper, we propose a near energy-optimal, stream processor family that relies on massively parallel, near-threshold VLSI circuits and interconnect, incorporating cooperative circuit/architecture techniques to tolerate the expected large delay variations. Initial estimations from circuit simulations show that it is possible to achieve greater than 1 Giga-Operations per second (1GOP/s) with less than 1mW total power consumption, enabling a new class of energy-constrained, high-throughput computing applications.

Green’s concept of an equivalent‐source layer is invoked to construct a data adaptive, zero‐phase, Wiener band‐pass filter for regional‐residual gravity anomaly separation. The observed gravity field’s Fourier power spectrum is modeled with two Green’s equivalent‐source layers, one equivalent layer for the shallower (residual field) geologic sources, and a second equivalent layer for the deeper (regional field) geologic sources. The depths and average physical property contrasts of the two equivalent layers are determined by fitting the observed gravity field’s Fourier power spectrum with a two‐layer spectral model. Each equivalent layer is simulated by a horizontal thin sheet with randomly varying and randomly distributed point density sources spread throughout it. Adopting such a theoretical model for the Fourier power spectrum yields a stable and well‐behaved filter transfer function. Like all band‐pass filtering though, the method is ineffective in the case of insufficient vertical separation between the shallow and deep geologic sources whose gravity anomalies it is desired to separate. The filter design process is simple and easily automated, being well‐suited for modular implementation in a “filter tool kit” applications program running on either a workstation or personal computer. Equally important, the method yields repeatable, interpreter‐independent results.

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