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  2. Time constant - Wikipedia

    en.wikipedia.org/wiki/Time_constant

    First order LTI systems are characterized by the differential equation + = where τ represents the exponential decay constant and V is a function of time t = (). The right-hand side is the forcing function f(t) describing an external driving function of time, which can be regarded as the system input, to which V(t) is the response, or system output.

  3. General time- and transfer constant analysis - Wikipedia

    en.wikipedia.org/wiki/General_time-_and_transfer...

    The general time- and transfer-constants (TTC) analysis [1] is the generalized version of the Cochran-Grabel (CG) method, [2] which itself is the generalized version of zero-value time-constants (ZVT), which in turn is the generalization of the open-circuit time constant method (OCT). [3]

  4. Exponential growth - Wikipedia

    en.wikipedia.org/wiki/Exponential_growth

    The growth constant k is the frequency (number of times per unit time) of growing by a factor e; in finance it is also called the logarithmic return, continuously compounded return, or force of interest. The e-folding time τ is the time it takes to grow by a factor e. The doubling time T is the time it takes to double.

  5. Rheobase - Wikipedia

    en.wikipedia.org/wiki/Rheobase

    The strength-duration time constant of both cutaneous and motor afferents decreases with age, and this corresponds to an increase in rheobase. [7] Two possible reasons for this age-related decrease in the strength-duration time constant have been proposed. First, nerve geometry might change with age because of axonal loss and neural fibrosis.

  6. RC time constant - Wikipedia

    en.wikipedia.org/wiki/RC_time_constant

    The RC time constant, denoted τ (lowercase tau), the time constant (in seconds) of a resistor–capacitor circuit (RC circuit), is equal to the product of the circuit resistance (in ohms) and the circuit capacitance (in farads):

  7. Gauss–Markov process - Wikipedia

    en.wikipedia.org/wiki/Gauss–Markov_process

    A stationary Gauss–Markov process with variance (()) = and time constant has the following properties.. Exponential autocorrelation: () = | |.; A power spectral density (PSD) function that has the same shape as the Cauchy distribution: () = +. (Note that the Cauchy distribution and this spectrum differ by scale factors.)

  8. Summation (neurophysiology) - Wikipedia

    en.wikipedia.org/wiki/Summation_(neurophysiology)

    If the time constant of the cell membrane is sufficiently long, as is the case for the cell body, then the amount of summation is increased. [6] The amplitude of one postsynaptic potential at the time point when the next one begins will algebraically summate with it, generating a larger potential than the individual potentials.

  9. Biot number - Wikipedia

    en.wikipedia.org/wiki/Biot_number

    in which = is the thermal time constant of the body, is the mass density (kg/m 3), and is specific heat capacity (J/kg-K). The study of heat transfer in micro-encapsulated phase-change slurries is an application where the Biot number is useful.