In a blind signal separation problem

for the purpose of algorithm selection and results evaluation

it is important to check the determinacy of the observation matrix.To the best of our knowledge

there is no available way to tell the determined case from the underdetermined one under the condition of full rank.To overcome this problem

we propose two methods based on ICA (independent component analysis) for determinancy check.In the first approach

we check the determinancy by looking into the independency of the output signals estimated by ICA.In theory

the outputs won't be independent in the underdetermined case

while in the determined case

the outputs will be independent if the source signals are independent.In the second approach

the observation data is windowed

and different windowed signal series are acquired by shifting the center of the rectangular window.when ICA is performed on the signal series

the basis vectors which are columns of the inverse of unmixing matrix are supposed to be stable in the determined case while unstable in the underdetermined case due to the variation of source signals’ statistical distribution.Experimental results show that our methods achieved good performance.