g by the inverse Fourier transform g = F t − $^{1}$( γ ), thus g is uniquely defined whenever γ is. Generally by this Theorem identification in deconvolution holds when- ever supp( φ ) = R $^{d}$. However, this excludes some error distributions such as the uniform or the triangular, where the characteristic function has isolated zeros. A more general result (Schwartz, 1966, pp.123-125) establishes the possibility of division by φ even when φ has zeros. In the one-dimensional case as long as φ is infinitely differentiable, the zeros are isolated and there exists a finite order derivative that is non-zero at every zero point of φ, any generalized function can be divided by φ. Thus since the uniform and triangular distributions have this property, deconvolution with these error distributions is also identified in S $^{∗}$. The next Theorem examines identification in the case when there are two unknown functions in the system (3) ; under Assumptions 1-3 it leads to (16). The main conditions are continuous differentiability of one of γ, or φ, assumptions about support and knowledge of the value of the differentiable function at an interior point. If that function is a characteristic function, its value at 0 is always 1. Theorem 3 Under Assumptions 1-3 for the system of equations (16) if supp( φ ) ⊃ supp( γ ) = W, where W is a connected set in R d that includes 0 as an interior point, and (a) if γ is continuously differentiable in W, γ (0) = c, then γ is uniquely 29