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updated docs
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<name>Optimization</name>
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<name>Optimization</name>
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<link>optimization_ex.cpp.html</link>
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<link>optimization_ex.cpp.html</link>
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</item>
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</item>
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<item>
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<name>Non-Linear Least Squares</name>
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<link>least_squares_ex.cpp.html</link>
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</item>
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<item>
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<item>
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<name>Kernel_RLS_Filtering</name>
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<name>Kernel_RLS_Filtering</name>
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<link>krls_filter_ex.cpp.html</link>
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<link>krls_filter_ex.cpp.html</link>
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This page documents library components that attempt to find the
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This page documents library components that attempt to find the
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minimum or maximum of a user supplied function. An introduction
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minimum or maximum of a user supplied function. An introduction
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to the general purpose non-linear optimizers in this section can be
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to the general purpose non-linear optimizers in this section can be
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found <a href="optimization_ex.cpp.html">here</a>.
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found <a href="optimization_ex.cpp.html">here</a>. For an example
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showing how to use the non-linear least squares routines look
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<a href="least_squares_ex.cpp.html">here</a>.
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</p>
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</p>
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</body>
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</body>
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@ -483,6 +485,9 @@ subject to the following constraint:
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large at the solution)
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large at the solution)
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</description>
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</description>
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<examples>
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<example>least_squares_ex.cpp.html</example>
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</examples>
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</component>
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</component>
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<!-- ************************************************************************* -->
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<!-- ************************************************************************* -->
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@ -498,6 +503,9 @@ subject to the following constraint:
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terms in the least squares function, the residuals, go to zero at the solution)
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terms in the least squares function, the residuals, go to zero at the solution)
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</description>
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</description>
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<examples>
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<example>least_squares_ex.cpp.html</example>
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</examples>
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</component>
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</component>
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<!-- ************************************************************************* -->
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<!-- ************************************************************************* -->
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