Fractal Time

In his latest work, Greg Braden, a former senior computer system designer and best-selling writer, summarized these ancient and modern world ideas into a powerful new time model.

He combines the modern law of the fractal model with the concept of the ancient cycle and shows everything from war and peace among nations to our most happy relationship and personal crisis. They are all our past regression models. When each mode returns, it has the same condition as the previous cycle - know fractal mode, measure and predict!

"New York Times" Best selling writer Greg Braden is an internationally renowned pioneer of bridge science and spirituality. After becoming a computer geologist of Phillips Oil during the energy crisis of the 1970s, he served as senior computer system designer for Martin Marietta in the last year of the Cold War. In 1991, he became the first technical operations manager at Cisco Systems and led the development of the global support team to ensure early Internet reliability. Greg has spent 22 years searching for alpine villages, distant monasteries, and forgotten sentences and discovering eternal secrets. So far, his work has been broken like "Isaiah effect", "God's code", "Holy matrix", and his recent "fractal time: the secret of 2012" and "the era of the New World" I brought an example. This Greg's work has been published in 27 languages ​​and 30 countries and there is no doubt that we have our key to the future in our past wisdom.

After presenting the case history of checking the accuracy of fractal time calculations, the authors answered questions that must be asked beyond traditional scientific and spiritual boundaries: About me since 2012 What is the fractal time telling them? Since this cycle is repeated, seeds of 2012 have already occurred and patterns already exist.

From the viewpoint of statistical dependence, fractal time series can be divided into two categories. One is LRD and the other is SRD. It can also be divided into Gaussian sequences or non-Gaussian sequences. The Gaussian fractal time series model is described in sections 4.1 to 4.4 and 4.6. Non-Gaussian series are explained in Section 4.5. FBm is commonly used to model transient fractal time series. It is Gauss (Sinai). The definition of fBm described in (2.18) is called Riemann-Liouville type because it uses the Riemann-Liouville integral (see, for example, Sithi and Lim, Muniandy and Lim, and Feyel and de la Pradelle) . That PSD is configured. Given the

Other articles are organized as follows. Section 2 describes the concept of fractal time series from the viewpoint of a fractional order system. The basic nature of the fractal time series is explained in Section 3. Several models of fractional time series are discussed in section 4. The conclusion is in section 5. On the other hand, it is possible to use a nonstationary random function as the output of the filter. Typically, under excitation of unsteady white noise, having different filters can create different series under excitation. Thus, traditionally, people are considered to be sources or sources of random sequences; for example, Press et al. checking ... . In this article, consider only fixed series