Abstract: Methods and systems for matching measurement spectra across one or more optical metrology systems are presented. The values of one or more system parameters used to determine the spectral response of a specimen to a measurement performed by a target metrology system are optimized. The system parameter values are optimized such that differences between measurement spectra generated by a reference system and the target system are minimized for measurements of the same metrology targets. Methods and systems for matching spectral errors across one or more optical metrology systems are also presented. A trusted metrology system measures the value of at least one specimen parameter to minimize model errors introduced by differing measurement conditions present at the time of measurement by the reference and target metrology systems. Methods and systems for parameter optimization based on low-order response surfaces are presented to reduce the compute time required to refine system calibration parameters.

Abstract: Methods and systems for matching measurement spectra across one or more optical metrology systems are presented. The values of one or more system parameters used to determine the spectral response of a specimen to a measurement performed by a target metrology system are optimized. The system parameter values are optimized such that differences between measurement spectra generated by a reference system and the target system are minimized for measurements of the same metrology targets. Methods and systems for matching spectral errors across one or more optical metrology systems are also presented. A trusted metrology system measures the value of at least one specimen parameter to minimize model errors introduced by differing measurement conditions present at the time of measurement by the reference and target metrology systems. Methods and systems for parameter optimization based on low-order response surfaces are presented to reduce the compute time required to refine system calibration parameters.

Abstract: Methods and systems for matching measurement spectra across one or more optical metrology systems are presented. The values of one or more system parameters used to determine the spectral response of a specimen to a measurement performed by a target metrology system are optimized. The system parameter values are optimized such that differences between measurement spectra generated by a reference system and the target system are minimized for measurements of the same metrology targets. Methods and systems for matching spectral errors across one or more optical metrology systems are also presented. A trusted metrology system measures the value of at least one specimen parameter to minimize model errors introduced by differing measurement conditions present at the time of measurement by the reference and target metrology systems. Methods and systems for parameter optimization based on low-order response surfaces are presented to reduce the compute time required to refine system calibration parameters.

Abstract: Methods and systems for matching measurement spectra across one or more optical metrology systems are presented. The values of one or more system parameters used to determine the spectral response of a specimen to a measurement performed by a target metrology system are optimized. The system parameter values are optimized such that differences between measurement spectra generated by a reference system and the target system are minimized for measurements of the same metrology targets. Methods and systems for matching spectral errors across one or more optical metrology systems are also presented. A trusted metrology system measures the value of at least one specimen parameter to minimize model errors introduced by differing measurement conditions present at the time of measurement by the reference and target metrology systems. Methods and systems for parameter optimization based on low-order response surfaces are presented to reduce the compute time required to refine system calibration parameters.

Abstract: In a recording/playback system, increased information is achieved by 4 level biased magnetic recording where the maximum amplitude 4 level recording signal drives the medium's magnetization into a nonlinear region of its transfer function. The bias does not eliminate distortion at the maximum signal input level, however the system's signal to noise ratio is improved due to an increase in the amplitude of the playback signal resulting from the increased recording level. The nonlinear mapping capability of a neural network provides equalization of playback signals distorted due to the record/playback nonlinearity. The 4 level recorded signals provide a factor of 2 in information storage compared to binary recording, and quadrature amplitude modulation (QAM) combined with the 4 level recording technique provides an additional factor of 2, for a factor of 4 in the information content stored.

Abstract: A chaotic carrier pulse position modulation communication system and method is disclosed. The system includes a transmitter and receiver having matched chaotic pulse regenerators. The chaotic pulse regenerator in the receiver produces a synchronized replica of a chaotic pulse train generated by the regenerator in the transmitter. The pulse train from the transmitter can therefore act as a carrier signal. Data is encoded by the transmitter through selectively altering the interpulse timing between pulses in the chaotic pulse train. The altered pulse train is transmitted as a pulse signal. The receiver can detect whether a particular interpulse interval in the pulse signal has been altered by reference to the synchronized replica it generates, and can therefore detect the data transmitted by the receiver. Preferably, the receiver predicts the earliest moment in time it can expect a next pulse after observation of at least two consecutive pulses.