Abstract: Systems and methods are described herein for generating representative cardiac information. The representative cardiac information may be based on a plurality of electrode signals monitored, or measured, over a plurality of cardiac cycles or heart beats. The systems and methods may remove unqualified cardiac cycles, remove invalid electrode signals, remove inconsistent cardiac cycles, and removing uncorrelated cardiac cycles, and then generate representative cardiac information based on the remaining cardiac cycles and electrode signals.

Abstract: A method for edge correction in pattern recognition includes generating a pattern recognition output for a pattern recognition process, including receiving, in the processor, a design layout, receiving a sample plan based on the design layout, receiving a first user-generated edge input, generating a pattern recognition recipe output from the design layout, the sample plan and the user-generated edge input, wherein the pattern recognition recipe output is configured to drive the pattern recognition process, generating a measurement model from the pattern recognition process, generating a measurement model pattern recognition output for an measurement model pattern recognition process, including receiving a second user-generated input and generating a measurement model pattern recognition recipe output from the measurement model and the second user-generated edge input, wherein the measurement model pattern recognition recipe output configured to drive the measurement model pattern recognition process.

Abstract: Exemplary embodiments include a method for edge correction in pattern recognition, the method including receiving a design layout, receiving a sample plan based on the design layout, receiving user-generated edge input and generating a recipe output from the design layout, the sample plan and the user-generated edge input. The incorporation of the edge input results in SEM recipes that are much more successful in recognizing patterns that have tendency to deviate in appearance from design by, for example, moderate to severe sidewall angle.

Abstract: A contour biasing method can include receiving contour input files, processing the contour input files, receiving contour measurements, receiving raw contour data, processing the raw contour data and outputting processed contour data based on the contour input files.

Abstract: Exemplary embodiments include a method for edge correction in pattern recognition, the method including receiving a design layout, receiving a sample plan based on the design layout, receiving user-generated edge input and generating a recipe output from the design layout, the sample plan and the user-generated edge input. The incorporation of the edge input results in SEM recipes that are much more successful in recognizing patterns that have tendency to deviate in appearance from design by, for example, moderate to severe sidewall angle.

Abstract: A method for edge correction in pattern recognition includes generating a pattern recognition output for a pattern recognition process, including receiving, in the processor, a design layout, receiving a sample plan based on the design layout, receiving a first user-generated edge input, generating a pattern recognition recipe output from the design layout, the sample plan and the user-generated edge input, wherein the pattern recognition recipe output is configured to drive the pattern recognition process, generating a measurement model from the pattern recognition process, generating a measurement model pattern recognition output for an measurement model pattern recognition process, including receiving a second user-generated input and generating a measurement model pattern recognition recipe output from the measurement model and the second user-generated edge input, wherein the measurement model pattern recognition recipe output configured to drive the measurement model pattern recognition process.