The results provide a better understanding of the interplay between bandwidth, element locations, weighting of the elements, pulse shape within the bandwidth, and imaging performance.
The quest to determine the atomic weights of elements occupied the greatest chemists of the 19th and early 20th centuries.
In 1815 Prout advanced the idea that the atomic weights of elements are whole-number multiples of the atomic weight of hydrogen (Prout's hypothesis).
The atomic weight of elements is a relative figure, with one atom of the carbon-12 isotope being assigned the atomic weight of 12; the atomic weight of hydrogen is then approximately 1, of oxygen approximately 16, and the molecular weight of water (H2O) 18.
Such weight of elements is beyond metacognitive thinking pattern of thought.
Utilization of them permits to reduce inertia and weight of elements up to 30% without diminutions of strength characteristics.
In this paper a class of matroidal combinatorial optimization problems with imprecise weights of elements is considered.
Daltonian atomism also predicts that if the weights of elements A and B that combine with a fixed weight of element C are x and y respectively, then if A and B combine to form a compound then the relative weights of A and B in the compound will be in the ration x:y or some simple multiple of it.
The weights of elements of the ground set are uncertain; for each element, an uncertainty interval that contains its weight is given.
In this case, one of the optimization problems is to find the sparsest array (number, locations, and weights of elements) for a given beampattern.
