Abstract: Methods for determining variance properties of a noise component of a raw signal of a machine or a system. An example method includes recording a signal using a noise estimation unit, numerically differentiating the signal using a first module of the noise estimation unit to obtain a differentiated signal, identifying, using a second module of the noise estimation unit, a histogram which corresponds to the differentiated signal, and determining using the histogram, a variance property of the noise component of the signal.

Abstract: Method for finding the probability density function type and the variance properties of the noise component N of a raw signal S of a machine or a system, said raw signal S being combined of a pure signal component P and said noise component N, the method comprising: (a) defining a window within said raw signal; (b) recording the raw signal S; (c) numerically differentiating the raw signal S within the range of said window at least a number of times m to obtain an m order differentiated signal; (d) finding a histogram that best fits the m order differentiated signal; (e) finding a probability density function type that fits the distribution of the histogram; (f) determining the variance of the histogram, said histogram variance being essentially the m order variance ?2(m) of the noise component N; and (g) knowing the histogram distribution type, and the m order variance ?2(m) of the histogram, transforming the m order variance ?2(m) to the zero order variance ?2(0), ?2(0) being the variance of the pdf of the n