The Development Cooperation Act (March 19, 2013) defines the consistency as a process to ensure that the objectives and results of Belgian development cooperation are not thwarted by other governmental policies which may produce an impact upon developing countries, and that other supported policies which may affect development goals.Īccording to the Organisation for Economic Cooperation and Development, Policy Coherence for Development provides a foundation to harness synergies and benefits in public policies in order to promote the utmost development of the poorest countries. S2CID 4494245.What is Policy Coherence for Development? 'Conversion from mild cognitive impairment to Alzheimer's disease is predicted by sources and coherence of brain electroencephalography rhythms'. 'Time estimation and beta segregation: An EEG study and graph theoretical approach'. ^ Ghaderi, Amir Hossein Moradkhani, Shadi Haghighatfard, Arvin Akrami, Fatemeh Khayyer, Zahra Balcı, Fuat (2018).'Cross spectral analysis of nonstationary processes'. Piersol, Random Data, Wiley-Interscience, 1986 The brain coherence during the rest state can be affected by disorders and diseases. Studies show that the coherence between different brain regions can be changed during different mental or perceptual states. Application in neural science Ĭoherence has been found a great application to find dynamic functional connectivity in the brain networks. For such signals, the concept of coherence has been extended by using the concept of time-frequency distributions to represent the time-varying spectral variations of non-stationary signals in lieu of traditional spectra. If the signals are non-stationary, (and therefore not ergodic), the above formulations may not be appropriate.

Additionally, noise introduced in the measurement process, or by the spectral signal processing can contribute to or corrupt the coherence.Įxtension to non-stationary signals In reality it is a combination of hydrological forcing from the ocean water levels and the tidal potential that are driving both the observed input and output signals.

We have also assumed that the ocean water levels drive or control the groundwater levels. For example, it is clear that the atmospheric barometric pressure induces a variation in both the ocean water levels and the groundwater levels, but the barometric pressure is not included in the system model as an input variable. Another common mistake is to assume a causal input/output relation between observed variables, when in fact the causative mechanism is not in the system model. If the relation ( transfer function) between the input and output is nonlinear, then values of the coherence can be erroneous. However, one must exercise caution in attributing causality. The computed coherence (figure 1) indicates that at most of the major ocean tidal frequencies the variation of groundwater level at this particular site is over 90% due to the forcing of the ocean tides. We further assume that the ocean surface height controls the groundwater levels so that we take the ocean surface height as the input variable, and the groundwater well height as the output variable. Let us assume that there is a linear relationship between the ocean surface height and the groundwater levels. To estimate the extent at which the groundwater levels are influenced by the ocean surface levels, we compute the coherence between them. It is clear that variation of the groundwater levels have significant power at the ocean tidal frequencies. The coherence (sometimes called magnitude-squared coherence) between two signals x(t) and y(t) is a real-valued function that is defined as: C x y ( f ) = | G x y ( f ) | 2 G x x ( f ) G y y ( f ) provides a spectral quantification of the output power that is uncorrelated with noise or other inputs.įigure 4: Autospectral density of groundwater well level. If the signals are ergodic, and the system function is linear, it can be used to estimate the causality between the input and output.

It is commonly used to estimate the power transfer between input and output of a linear system. In signal processing, the coherence is a statistic that can be used to examine the relation between two signals or data sets.

Coherence means