Marvasti
Farokh Marvasti, Tehran IR
Patent application number | Description | Published |
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20090027249 | A/D CONVERTERS BASED ON SIGMA DELTA MODULATORS AND ITERATIVE METHODS - A system and method is provided to improve the performance of the sigma delta analog to digital converter (ADC). An input signal analog signal received though an input device is passed to a sigma delta modulator (SDM). The output of the modulator is passed through a low pass filter. An iterative algorithm and acceleration algorithm are applied to process the filter output signals to shape the noise components and to improve the performance of the sigma delta ADC. A distortion operator such as G operator, comprising of sigma delta modulator and multistage low pass filter (LPF) is used to suppress the shaped quantization noise. | 01-29-2009 |
20090285125 | Iterative synchronous and Asynchronous Multi-User Detection with Optimum Soft limiter - An iterative method for multi-user detection in Code Division Multiple Access (CDMA) Systems is used to improve the capacity of the network for random codes. A soft limiter function is used in the output of each step of iterations to accelerate the convergence and also to improve the interference cancellation power of this method. | 11-19-2009 |
Farokh Marvasti, London GB
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20120257640 | Uniquely Decodable Codes And Decoder for Overloaded Synchronous CDMA Systems - A recursive method for constructing uniquely decodable codes for overloaded synchronous CDMA systems, where large signature codes with growing overloading factors are reconstructed from the small ones. A class of uniquely decodable signature matrices (or encoders) for overloaded synchronous CDMA are also devised. A decoder for synchronous CDMA systems to extract the user data by a number of comparisons with respect to some predefined thresholds. | 10-11-2012 |
Mazda A. Marvasti, Coto De Caza, CA US
Patent application number | Description | Published |
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20110119029 | Nonparametric Method for Determination of Anomalous Event States in Complex Systems Exhibiting Non-Stationarity - According to a feature of the present disclosure, a method is provided for the determination of anomalous events in complex systems, such as problems, inefficiencies, and failures, and a tool is provided for the detection of these events. Many complex systems are non-stationary or experience periodic fluctuations or spikes in values that are outside of normal ranges, but constitute normal behavior nevertheless. The method accounts for both non-stationarity, as well as fluctuations and spikes. Additional novel features include both a threshold setting initialization method and a regression method for the determination of the start points and end points of events. | 05-19-2011 |
20130097125 | AUTOMATED ANALYSIS OF UNSTRUCTURED DATA - The current application is directed to automated methods and systems for processing and analyzing unstructured data. The methods and systems of the current application identify patterns and determine characteristics of, and interrelationships between, events parsed from the unstructured data without necessarily using user-provided or expert-provided contextual knowledge. In one implementation, the unstructured data is parsed into attributed-associated events, reduced by eliminating attributes of low-information content, and coalesced into nodes that are incorporated into one or more graphs, within which patterns are identified and characteristics and interrelationships determined. | 04-18-2013 |
20130097463 | METHOD AND APPARATUS FOR ROOT CAUSE AND CRITICAL PATTERN PREDICTION USING VIRTUAL DIRECTED GRAPHS - An approach to root cause determination in a complex systems based on monitoring and event data is disclosed. It includes a historical analysis of events with their probabilistic correlations. Applying information measures between the random variables which embody those events one can detect origins of problems and generate real-time recommendations for their locations in a hierarchical system. Estimation of system bottlenecks, as well as the risk of “black swan”-type events are also computed. The processes are based on a statistical processing of a virtual directed graph produced from historical events. | 04-18-2013 |
Mazda A. Marvasti, Irvine, CA US
Patent application number | Description | Published |
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20140053025 | METHODS AND SYSTEMS FOR ABNORMALITY ANALYSIS OF STREAMED LOG DATA - This disclosure presents systems and methods for run-time analysis of streams of log data for abnormalities using a statistical structure of meta-data associated with the log data. The systems and methods convert a log data stream into meta-data and perform statistical analysis in order to reveal a dominant statistical pattern within the meta-data. The meta-data is represented as a graph with nodes that represent each of the different event types, which are detected in the stream along with event sources associated with the events. The systems and methods use real-time analysis to compare a portion of a current log data stream collected in an operational window with historically collected meta-data represented by a graph in order to determine the degree of abnormality of the current log data stream collected in the operational window. | 02-20-2014 |
20140298098 | DATA-AGNOSTIC ANOMALY DETECTION - This disclosure presents computational systems and methods for detecting anomalies in data output from any type of monitoring tool. The data is aggregated and sent to an alerting system for abnormality detection via comparison with normalcy bounds. The anomaly detection methods are performed by construction of normalcy bounds of the data based on the past behavior of the data output from the monitoring tool. The methods use data quality assurance and data categorization processes that allow choosing a correct procedure for determination of the normalcy bounds. The methods are completely data agnostic, and as a result, can also be used to detect abnormalities in time series data associated with any complex system. | 10-02-2014 |