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Estimation theory. Estimation theory is a branch of statistics that deals with estimating the values of parameters based on measured empirical data that has a random component. The parameters describe an underlying physical setting in such a way that their value affects the distribution of the measured data. An estimator attempts to approximate ...
Time series. In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily ...
Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [1][2][3] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields such as ...
Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing signals, such as sound, images, potential fields, seismic signals, altimetry processing, and scientific measurements. [1] Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted ...
In statistics, econometrics, and signal processing, an autoregressive (AR) model is a representation of a type of random process; as such, it can be used to describe certain time-varying processes in nature, economics, behavior, etc. The autoregressive model specifies that the output variable depends linearly on its own previous values and on a ...
William A Gardner (born Allen William Mclean, November 4, 1942) is a theoretically inclined electrical engineer who specializes in the advancement of the theory of statistical time-series analysis and statistical inference with emphasis on signal processing algorithm design and performance analysis. [1] He is also an entrepreneur, a professor ...
Pattern recognition is the task of assigning a class to an observation based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess (PR) capabilities but their primary function is to distinguish and create emergent patterns. PR has applications in statistical ...
Sergio Verdu. Xiaodong Wang. Harold Vincent Poor is the Michael Henry Strater University Professor of Electrical Engineering at Princeton University, where he is also the Interim Dean of the School of Engineering and Applied Science. [3][4] He is a specialist in wireless telecommunications, signal processing and information theory. [5]