information may also be integrated through inequality constraints on the model parameters or some functions of them. Such constraints are important to avoid unrealistic values for the parameters (negative values for instance). In this case, the space spanned by model parameters will no longer be a vector space but a subset of admissible models denoted by in the sequel.

Tools to overcome the second difficulty

As mentioned above, noise may be such that our measurements are not the image of any model, so that we cannot

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