e or a parcel, comprising the steps of:
(a) teaching an Artificial Neural System (ANS) how to detect the presence of said prescribed material within said object based on a quantitative analysis of particular emissions emitted from said prescribed material when irradiated with radiant energy, said ANS comprising a plurality of layers of processors connected in a parallel network, said teaching including adjusting the interconnections between said processors with an appropriate weighting factor; and
(b) presenting emissions from said object to the ANS trained in step (a), whereby the ANS detects whether said prescribed material is present within said object.
9. The method of claim 8 wherein the step of teaching said ANS includes the iterative process of:
(1) presenting the emissions emitted from a first configuration of said prescribed material to an input processor layer of said ANS,
(2) incrementally adjusting selected weighting factors of said ANS until an output processor layer of said ANS signals the detection of said prescribed material,
(3) repeating steps (1) and (2) for additional configurations of said prescribed material, and
(4) repeating steps (1) through (3) a sufficient number of times to train the ANS to correctly detect said prescribed material for all tested configurations.
10. A method for non-invasively detecting explosives in an object under investigation comprising the steps of:
(a) generating thermal neutrons;
(b) irradiating said object with said thermal neutrons, the interactions of said thermal neutrons with atomic nuclei within said object giving rise to the emission of gamma rays, said gamma rays having an energy level characteristic of the nuclear species contained in said object;
(c) detecting emitted gamma rays having an energy level characteristic of at least one specific element and the approximate location of the origin of said gamma rays within said object, thereby providing a measure of the density distribution of said at least one specific element within said object;
(d) detecting neutrons that pass through said object without substantially interacting with atomic nuclei, the detection of said neutrons thereby providing a rough measure of the density distribution of most nuclear species within said object;
(e) generating a three-dimensional elemental density image of said object based upon the density distributions obtained from steps (c) and (d); and
(f) determining whether said three-dimensional elemental density image indicates the presence of explosives within said object.
11. The method of detecting explosives as set forth in claim 10 wherein step (c) includes rejecting background noise in the spectrum of detected gamma rays, said background noise including gamma rays that are emitted from non-explosive elements within said object and its surrounding environment.
12. The method of detecting explosives as set forth in claim 11 wherein said means for rejecting background noise includes measuring background noise at a first region in the spectrum of detected gamma rays and subtracting said background noise from a second region in the spectrum of the detected gamma rays, said second region in the gamma ray spectrum corresponding to gamma rays resulting from neutron interaction with nitrogen nuclei.
13. The method of detecting explosives as set forth in claim 10 further including generating at least one two-dimensional electron density image of said object; and using said electron density image in combination with said three-dimensional elemental density image to help confirm the presence of explosives within said object.
14. The method of detecting explosives as set forth in claim 13 wherein the step of generating at least one two-dimensional electron density image of said object comprises generating two two-dimensional electron density images of said object, a first electron density image lying in a first plane, and a second electron density image lying in a second plane that is orthogonal to said first plane, whereby the combination of said first and second electron density images pr