Application of optimum linear filter theory to the detection of cortical signals preceding facial movement in cat

1973 ◽  
Vol 16 (5) ◽  
pp. 455-465 ◽  
Author(s):  
C. D. Woody ◽  
M. J. Nahvi
Keyword(s):  
Linear Filter ◽  
Facial Movement ◽  
Filter Theory

To: “Direct Interpretation of Geoelectric Measurements by the Use of Linear Filter Theory,” by Sri Niwas, GEOPHYSICS, v. 40, p. 121–122.

Geophysics ◽  
1975 ◽  
Vol 40 (5) ◽  
pp. 886-886
Keyword(s):  
Linear Filter ◽  
Filter Theory ◽  
Direct Interpretation

In the article, “Direct Interpretation of Geoelectric Measurements by the Use of Linear Filter Theory”, by Sri Niwas, Geophysics, v. 40, p. 121–122, the following corrections should be made: (1) In Figure 1, the Y-axis is in fact the Z-axis, and the Z-axis is the Y-axis (as referred to in the text). (2) In Figure 1, the resistivity of the dike is [Formula: see text] and that of the subsequent medium is [Formula: see text]. (3) Equation (9) should be [Formula: see text]

DIRECT INTERPRETATION OF GEOELECTRIC MEASUREMENTS BY THE USE OF LINEAR FILTER THEORY

Geophysics ◽  
1975 ◽  
Vol 40 (1) ◽  
pp. 121-122 ◽  
Author(s):  
Sri Niwas
Keyword(s):  
Kernel Function ◽  
Apparent Resistivity ◽  
Linear Filter ◽  
Intermediate Step ◽  
Electrical Measurements ◽  
Filter Theory ◽  
Direct Interpretation ◽  
Order Of Magnitude ◽  
Electrical Soundings

In a recent paper Lee and Green (1973) worked out a method for direct interpretation of electrical soundings made over a fault or dike (see Figure 1). They computed the kernel function using the method developed by Meinardus (1970). However, Koefoed (1968), while dealing with direct interpretation of electrical measurements made over a horizontally layered earth, showed that the relative variations in the apparent resistivity were not of the same order of magnitude in the corresponding kernel curve; thus, any method based on the determination of this function as the intermediate step would lead to a loss of information and hence to incorrect interpretation. Koefoed (1970) introduced a function T(λ) called the resistivity transform (a function related to the kernel function) as an intermediate step. Ghosh (1971) used linear filter theory and gave a simple and quick procedure to obtain the T(λ) function from the apparent resistivity field curve. He cited the properties of the T function as, (1) it is solely determined by the layer distribution; (2) it is an unambiguous representation of the [Formula: see text] function; and (3) for small and large values of 1/λ it approaches the [Formula: see text] curves.

The use of comparison filters in linear filter theory

1983 ◽  
Vol 24 (11) ◽  
pp. 2550-2552 ◽  
Author(s):  
Harry E. Moses
Keyword(s):  
Linear Filter ◽  
Filter Theory

Recent Progress and Plans in Computer-Controlled High Resolution Electron Microscopy

1990 ◽  
Vol 48 (1) ◽  
pp. 154-155
Author(s):  
W.J. de Ruijter ◽  
Peter Rez ◽  
David J. Smith
Keyword(s):  
Electron Microscopy ◽  
Digital Processing ◽  
High Resolution Electron Microscopy ◽  
Objective Lens ◽  
Linear Filter ◽  
Contrast Transfer Function ◽  
Image Displacement ◽  
Spatially Resolved ◽  
Wide Range ◽  
On Line

Digital computers are becoming widely recognized as standard accessories for electron microscopy. Due to instrumental innovations the emphasis in digital processing is shifting from off-line manipulation of electron micrographs to on-line image acquisition, analysis and microscope control. An on-line computer leads to better utilization of the instrument and, moreover, the flexibility of software control creates the possibility of a wide range of novel experiments, for example, based on temporal and spatially resolved acquisition of images or microdiffraction patterns. The instrumental resolution in electron microscopy is often restricted by a combination of specimen movement, radiation damage and improper microscope adjustment (where the settings of focus, objective lens stigmatism and especially beam alignment are most critical). We are investigating the possibility of proper microscope alignment based on computer induced tilt of the electron beam. Image details corresponding to specimen spacings larger than ∼20Å are produced mainly through amplitude contrast; an analysis based on geometric optics indicates that beam tilt causes a simple image displacement. Higher resolution detail is characterized by wave propagation through the optical system of the microscope and we find that beam tilt results in a dispersive image displacement, i.e. the displacement varies with spacing. This approach is valid for weak phase objects (such as amorphous thin films), where transfer is simply described by a linear filter (phase contrast transfer function) and for crystalline materials, where imaging is described in terms of dynamical scattering and non-linear imaging theory. In both cases beam tilt introduces image artefacts.

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