WIP: Fast Minimum Variance beamformer (postprocess.fast_minimum_variance) - #37
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…pper has residual mismatch Status: - Core MV algorithm (covariance, weights, application) verified pixel-by-pixel to produce IDENTICAL results to capon_minimum_variance_implementation - But when called through go(), output differs by factor ~1.85x - Issue is NOT in: K_samples, L_elements, data_cube values, R matrices, or normalization - Issue likely in: how input.data dimensions are indexed in the go() loop (possibly a subtle 3D vs 4D squeeze/reshape edge case) Files: - +postprocess/fast_minimum_variance.m: full implementation with debug prints - examples/advanced_beamforming/fast_minimum_variance_example.m: validation script Co-authored-by: Ole Marius Hoel Rindal <olemarius90@users.noreply.github.com>
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WIP: Fast Minimum Variance Beamformer
Efficient reimplementation of
postprocess.capon_minimum_varianceas a drop-in replacement.Status: debugging go() wrapper mismatch
What works:
dimension,K_in_lambda,L_elements,regCoef,doForwardBackwardKnown issue:
go(), output differs from reference by a consistent factor ~1.85xh.input.dataor stores resultsFiles
+postprocess/fast_minimum_variance.m— implementationexamples/advanced_beamforming/fast_minimum_variance_example.m— validation script comparing against referenceNext steps