Abstract: Computer-implemented methods, systems and products for analytics and discovery of patterns or signals. The method includes a set of operations or steps, including collecting data from a plurality of data sources, the data having a plurality of associated data types, and filtering the collected data based on identifying viable data sources from which the data is collected. The method further includes prioritizing discovery objectives based on analyzing the filtering results, and enriching the filtered collected data from viable data sources according to the prioritized discovery objectives. The method further includes extracting one or more signals from the enriched data using one or more machine learning mechanisms in combination with qualified subject matter expertise input, and graphically displaying the extracted signals in a meaningful way to a human operator such that the human operator is enabled to understand importance of extracted signals.

Abstract: An improved level shifter is disclosed. The level shifter is able to achieve a switching time below 1 ns using a relatively low voltage for VDDL, such as 0.75 V. The improved level shifter comprises a coupling stage and a level-switching stage. A related method of level shifting is also disclosed.

Abstract: An improved level shifter is disclosed. The level shifter is able to achieve a switching time below 1 ns using a relatively low voltage for VDDL, such as 0.75V. The improved level shifter comprises a coupling stage and a level-switching stage. A related method of level shifting is also disclosed.

Abstract: An improved level shifter for use in integrated circuits is disclosed. The level shifter is able to achieve a switching time below 1 ns while still using the core power supply voltages, VDDL and VDDH, used in the prior art. The improved level shifter comprises a coupling stage and a level-switching stage.