Frequency Awareness

Jean Baptiste Joseph Fourier

Frequency Awareness presents Minds of Genius, a series of informational articles to help explain the history of energetic medicine. In this article we discuss Jean Baptiste Joseph Fourier and the Fournier Analysis and Amplitude. Amplitude is connected to the Quantum Biofeedback technology.

With this basic informational background, it is intented the reader will gain insight to the services provided by Frequency Awareness such as the Quantum Biofeedback, Auric Clearings, Karma Removal, Seal Removal, Codependency Karma Removal, Victimization Karma Removal, DNA Activations, Parental/Ancestral Karma Removal and Ascension DNA Activation as they are remote sessions working through the quantum field and working with the body electric. The information is provided for basic educational purposes only and is intended to spark interest for further study and research.

Jean Baptiste Jospeh Fourier (March 21, 1768 - May 16, 1830) was a French mathematician and physicist who is best known for initiating the investigation of Fourier series and their application to problems of heat flow.  The Fourier transform is also named in his honour.  Fourier is also generally credited with the discovery of the greenhouse effect.  Fourier is the founder of these complex mathematical equations that allow us to separate complex waves into simple wave forms.

In mathematics, a Fourier series decomposes a periodic function into a sum of simple oscillating functions, namely sines and cosines.  The study of Fourier series is a branch of Fourier analysis.  Fourier analysis, named after Joseph Fourier's introduction of the Fourier series, is the decomposition of a function in terms of sinusoidal functions (called basis functions) of different frequencies that can be recombined to obtain the original function.  The recombination process is called Fourier synthesis (in which case, Fourier analysis refers specifically to the decomposition process).  The result of the decomposition is the amount (i.e. amplitude) and the phase to be imparted to each basis function (each frequency) in the reconstruction.  It is therefore also a function (of frequency), whose value can be represented as a complex number, in either polar or rectangular coordinates.  And it is referred to as the frequency domain representation of the original function.  A useful analogy is the sound produced by a musical chord and the set of musical notes (the frequency components) that it comprises.  The term Fourier transform can refer to either the frequency domain representation of a function or to the proess/formula that "transforms" one function into the other.  However, the transform is usually given a more specific name depending upon the domain and other properties of the function being transformed, as elaborated below.  Moreover, the original concept of Fourier analysis has been extended over time to apply to more and more abstract and general situations, and the general field is often known as harmonic analysis.

In terms of signal processing, the transform takes a time series representation of a signal function and maps it into a frequency spectrum, where w is angular frequency.  That is, it takes a function in the time domain into the frequency domain; it is a decomposition of a function into harmonics of different frequencies.

When the function f is a function of time and represents a physical signal, the transform has a standard interpretation as the frequency spectrum of the signal.  The magnitude of the resulting complex-valued function F at frequency w represents the amplitude of a frequency component whose initial phase is given by: arctan (imaginary part/real part).

However, it is important to realize that Fourier transforms are not limited to functions of time, and temporal frequencies.  They can equally be applied to analyze spatial frequencies, and indeed for nearly any function domain.  When processing signals, such as audio, radio waves, light waves, seismic waves, and even images.  Fourier analysis can isolate individual components of a compound waveform, concentrating them for easier detection and/or removal.  A large family of signal processing techniques consist of Fourier-transforming a signal, manipulating the Fourier-transformed data in a simple way, and reversing the transformation.