Convex set for similarity constraint

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SUMMARY

The discussion focuses on finding a projector onto a convex set defined by correlation constraints in a Hilbert Space for seismic processing applications. The convex set, denoted as C, requires that each signal u(t) correlates with every other signal v(t) above a scalar threshold ρ, given a known signal w(t) is included in C. The challenge lies in the self-referential definition of C, which complicates the formulation of the projector P onto this set.

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Squatchmichae
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I am trying to ultimately find the projector onto a convex set defined in a non-explicit way, for a seismic processing application.

The signals in question are members of some Hilbert Space H and the set membership requires that they must correlate with each other above some scalar \rho, given that the known signal \textbf{w} is in the set. Symbolically, I want to find a projector \textit{P} onto the convex set \textit{C}:

\begin{equation}

C = \left\{\mathbf{u}(t) : \left\langle \hat{\mathbf{u}}(t),\hat{\mathbf{v}}(t) \right\rangle \geq\rho_{0}, \forall \mathbf{v}(t) \in C, \quad where \quad \mathbf{w}(t) \in C \right\},

\end{equation}

Any intermediate help is appreciated, i.e., is there an equivalent way to formulate this set, that make finding the projector easier?
 
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I'm a bit confused by how C references itself in its definition.
 
Office_Shredder said:
I'm a bit confused by how C references itself in its definition.

I understand the confusion--that is what makes the defining characteristic a little awkward. The basic idea is this: each element in the convex set \textit{C} must correlate with every other element above \rho. But we also know that a given (known) element \textbf{w}(t) is contained in \textit{C}. Is that less confusing of a statement?
 

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