Abstract: A method reconstructs a signal by sampling the signal using a sampling procedure to obtain an input signal. A consistent set is determined from the input signal including the first elements such that applying the sampling procedure to the first elements results in the input signal. According to the type of the signal, a guiding set is determined including second elements disjoint from the first elements. A reconstruction set including third elements is generated so that the third elements minimize a sum of a first similarity measure of the third elements to the second elements and a second similarity measure of the third elements to the first elements. A transformed signal that minimizes a function on the reconstruction set is determined. A reconstructed signal is rendered so that a third similarity measure of the reconstructed signal to the transformed signal is smaller than a tolerance.

Abstract: Anomalies in real time series are detected by first determining a similarity matrix of pairwise similarities between pairs of normal time series data. A spectral clustering procedure is applied to the similarity matrix to partition variables representing dimensions of the time series data into mutually exclusive groups. A model of normal behavior is estimated for each group. Then, for the real time series data, an anomaly score is determined, using the model for each group, and the anomaly score is compared to a predetermined threshold to signal the anomaly.

Abstract: Data points of input data are processed by first determining a Laplacian matrix for the data. A spectrum of the Laplacian matrix includes an attractive spectrum of positive eigenvalues, a repulsive spectrum of negative eigenvalues, and a neutral spectrum of zero eigenvalues. An operation for the processing is determined using the Laplacian matrix, using information about the attractive spectrum, the repulsive spectrum, and the neutral spectrum, wherein the information includes the spectra and properties derived from the Spectra. Then, the operation is performed to produce processed data.

Abstract: A method processes a signal by first constructing a graph from the signal, and then determining a graph matrix from the graph and the signal. A Krylov-based subspace is determined based on the graph matrix and the signal. A filter for the Krylov subspace is determined. The filter transforms the signal to produce a filtered signal, which is output.

Abstract: A method for a continuation model predictive control (CMPC) of a system determines at least a part of a preconditioner using an approximate coefficient function and determines a solution vector by solving a matrix equation of the CMPC with a coefficient matrix defined by an exact coefficient function at a current time step of a control using an iterative method with the preconditioner. The approximate coefficient function applied to a vector approximates a result of an application of the exact coefficient function to the vector. A control signal for controlling the system is generated using the solution vector.

Abstract: A method modulates data for optical communication by first encoding the data using a forward error correction (FEC) encoder to produce encoded data, which are encoded using a block encoder to produce block encoded data such that Hamming distances between code words that represent the block encoded data are increased. The block encoded data are mapped to produce mapped data such that Euclidian distances between the constellation points are increased. Then, the mapped data are modulated in a transmitter to a modulated signal for an optical channel.

Abstract: A method analyzes traps in a semiconductor device by determining a first-order derivative of a signal representing an operation of the semiconductor device over time to produce a signal rate change. The traps in the semiconductor device are analyzed based on lifetimes corresponding to peaks of the signal rate change.

Abstract: A method determines a defect on a surface of an object. A symmetric representation of at least part of the object is generated and a pair of unmatched areas between the surface of the object and a surface of the symmetric representation is determined. Next, the defect on the surface of the object is determined based on the pair of unmatched areas.