Let f: Δ ⊆ ℝ2 → ℝ be a partial differentiable mapping on Δ: = [a, b] × [c, d] with a < b, c < d.
Let f : Δ = [a, b] × [c, d] → ℝ be a partial differentiable mapping on Δ = [a, b] × [c, d].
Theorem 7. Let f : Δ = [a, b] × [c, d] → ℝ be a partial differentiable mapping on Δ = [a, b] × [c, d].
Let f : Δ ⊂ ℝ2 → ℝ be a partial differentiable mapping on Δ := [a, b] × [c, d] in ℝ2 with a < b and c < d.
Theorem 2. Let f: Δ ⊆ ℝ2 → ℝ be a partial differentiable mapping on Δ:= [a, b] × [c, d] with a < b, c < d.
Theorem 7. Let f : Δ ⊂ ℝ2 → ℝ be a partial differentiable mapping on Δ := [a, b] × [c, d] in ℝ2 with a < b and c < d.
Now we state our next result in: Theorem 4. Let f: Δ ⊆ ℝ2 → ℝ be a partial differentiable mapping on Δ: = [a, b] × [c, d] with a < b, c < d.
In [16], Sarıkaya et al. proved some Hadamard-type inequalities for co-ordinated convex functions as following: Theorem 2. Let f : Δ ⊂ ℝ2 → ℝ be a partial differentiable mapping on Δ := [a, b] × [c, d] in ℝ2with a
Theorem 3. Let f : Δ ⊂ ℝ2 → ℝ be a partial differ entiable mapping on Δ := [a, b] × [c, d] in ℝ2with a
Three cases in which a partial mapping is obtained can be identified: 1) a consumed data item is simply not used by the connector to produce an output; 2) a consumed data item may represent part of the information used by the connector to produce an output; and 3) a concept representing a produced item may be derived from the input data.
