
...this demo, we present the streamfitter system for realtime linear regression analysis on continuous data streams. in order
to perform regression on data streams, it is necessary to continuously...we will present two approaches for online, multidimensional linear regression analysis of stream data, namely
incremental mathematical stream regression (imsr) and approximate stream regression (asr). these methods dynamically recompute...

...this demo, we present the streamfitter system for realtime linear regression analysis on continuous data streams. in order
to perform regression on data streams, it is necessary to continuously...we will present two approaches for online, multidimensional linear regression analysis of stream data, namely
incremental mathematical stream regression (imsr) and approximate stream regression (asr). these methods dynamically recompute...

...its application to clinical populations. a system is described that addresses the need for rapid analysis of fmri data and lays the foundation for dealing with problems that impede the application of fmri to clinical populations. the system, i/owa (input/output timeaware architecture), com bines a general architecture for sampling and timestamping relevant information channels in...

...paper we motivate the need for and research issues arising from a new model of data processing. in this model, data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, timevarying data streams. in addition to reviewing past work relevant to data stream systems and current projects in the...

...abstract—we introduce pulse, a framework for processing continuous queries over models of continuoustime data, which can compactly,and,accurately represent,many,realworld activities and processes. pulse...which we fully implemented,in a stream,processing,system. we,then characterise pulse’s behavior through experiments with real data, including financial data from the new york stock...

...lt;p>a key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be...can extract particular aspects needed for diverse tasks in realtime. stable internal states are not required for giving a stable output, since transient internal...

...learn ing problems that require realtime performance from an essentially infinite stream of incrementally arriving data. this paper demonstrates how even...validation allows  to our knowledge for the first time  implementing inverse dynamics learning for such a complex robot with realtime performance. in our sample task...

...in mine. how to make realtime detection of abnormal data in mine microseisms positioning system is a extremely important task. forecast model and mechanism of data stream in the mine microcosmic monitoring system are given through the linear selfregression analysis. based on this prediction model...

...have more than very large data bases; they have databases that grow without limit at a rate of several million records...set of experiments on synthetic data. we apply vfdt to mining the continuous stream of web access data from the whole university of...

...to analyze and mine such data in realtime. statistical methods frequently form the core of realtime analysis and therefore statisticians increasingly encounter...supplemental materials detail the computing systems typically used for streaming systems with realtime constraints and the process of optimizing code for high efficiency and throughput....