# Numerical Solution of a Non-Linear Volterra Integral Equation

## Abstract

In this paper, a numerical method to solve non-linear integral equations based on a successive approximation technique is considered. A sequence of functions is produced which converges to the solution. The process includes a fixed point method, a quadrature rule, and an interpolation method. To find a total bound of the error, we investigate error bounds for each approximation and by combining them, we will derive an estimate for the total error. The accuracy and efficiency of the method is illustrated in some numerical examples.

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1. 1.

For h = f and w = v we write T 0 x shortly for T 0(f, v, x).

2. 2.

Condition (28) is an assumption on the smallness of the data (cf. (4)) which is similar but slightly more strict than assumption (b) in Theorem 5.

3. 3.

Note that in computations the evaluation of $$\|g-I_{\Delta }g\|_{C^{0}(\tau )}$$, typically, has to be replaced by the maximum over |(gI Δ g)(t τ, i )| for a finite set {t τ, i :1≤in τ }⊂τ.

4. 4.

From (57) it follows that

$$\frac{h_{\ell}}{h_{\ell-1}}=\frac{h_{\tau_{\ell+1}}+h_{\tau_{\ell}}}{h_{\tau_{\ell-1}}+h_{\tau_{\ell}}}\leq\frac{1+\kappa}{1+\frac{1}{\kappa}}=\kappa.$$

## References

1. 1.

Agarwal, R.P., O’Regan, D., Wong, P.J.Y.: Positive Solutions of Differential, Difference and Integral Equations. Kluwer Academic, Dordrecht (1999)

2. 2.

Appell, J., Zabrejko, P.P.: Nonlinear Superposition Operators. Cambridge Tracts in Mathematics, vol. 95. Cambridge University Press, Cambridge (1990)

3. 3.

Banaś, J., Goebel, K.: Measures of Noncompactness in Banach Spaces, vol. 60. Marcel Dekker, New York (1980)

4. 4.

Banaś, J., Martinon, A.: Monotone solutions of a quadratic integral equation of Volterra type. Comput. Math. Appl. 47, 271–279 (2004)

5. 5.

Banaś, J., Olszowy, L.: Measures of noncompactness related to monotonicity. Comment. Math. 41, 13–23 (2001)

6. 6.

Banaś, J., Rzepka, B.: On existence and asymptotic stability of solutions of a nonlinear integral equation. J. Math. Anal. Appl. 284, 165–173 (2003)

7. 7.

Banaś, J., Sadarangani, K.: Monotonicity properties of the superposition operator and their applications. J. Math. Anal. Appl. 340, 1385–1394 (2008)

8. 8.

Burden, R.L., Faires, J.D.: Numerical Analysis, 8th edition. Cengage learning (2005)

9. 9.

Burton, T.A.: Volterra Integral and Differential Equations. Academic Press, New York (1983)

10. 10.

Carey, G.F., Dinh, H.T.: Grading functions and mesh redistribution. SIAM J. Numer. Anal. 22, 1028–1040 (1985)

11. 11.

Deimling, K.: Nonlinear Functional Analysis. Springer-Verlag, Berlin (1985)

12. 12.

Kershaw, D: A note on the convergence of interpolatory cubic splines. SIAM J. Numer. Anal. 8, 67–74 (1971)

13. 13.

Maleknejad, K., Nouri, K., Mollapourasl, R.: Existence of solutions for some nonlinear integral equations. Commun. Nonlinear Sci. Numer. Simul. 14, 2559–2564 (2009)

14. 14.

Maleknejad, K., Nouri, K., Mollapourasl, R.: Investigation on the existence of solutions for some nonlinear functional-integral equations. Nonlinear Anal. 71, 1575–1578 (2009)

15. 15.

Maleknejad, K., Mollapourasl, R., Nouri, K.: Study on existence of solutions for some nonlinear functional-integral equations. Nonlinear Anal. 69, 2582–2588 (2008)

16. 16.

Maleknejad, K., Torabi, P., Mollapourasl, R.: Fixed point method for solving nonlinear quadratic Volterra integral equations. Comput. Math. Appl. 62, 2555–2566 (2011)

17. 17.

Mathews, J.H., Fink, K.D.: Numerical Methods Using Matlab, 4th edition. Prentice-Hall Inc, New Jersey (2004)

18. 18.

O’Regan, D., Meehan, M.: Existence Theory for Nonlinear Integral and Integro-Differential Equations. Kluwer Academic, Dordrecht (1998)

19. 19.

Stoer, J., Bulirsch, R.: Introduction to Numerical Analysis, 3rd edition. Springer-Verlag, New York (2002)

## Author information

Authors

### Corresponding author

Correspondence to S. Sauter.

Dedicated to Professor Eberhard Zeidler on the occasion of his 75th birthday.

## Appendix: Stability and Convergence of Cubic Spline Interpolation

### Theorem 11

For an interval partitioning

$$0=t_{0}<t_{1}<\cdots<t_{N}=1,\quad\tau_{i}:=[t_{i-1},t_{i}],\quad h_{\tau_{i}}:=t_{i}-t_{i-1}$$

with corresponding function values $$\mathbf {f}:=(f_{i})_{i=0}^{N}$$, let u Δ denote the cubic interpolating spline with boundary conditions

$$u_{\Delta}^{\prime}(0)=\frac{f_{2}-f_{0}}{t_{2}-t_{0}}\quad\text{ and }\quad u_{\Delta}^{\prime}(1) =\frac{f_{N}-f_{N-2}}{t_{N}-t_{N-2}}.$$
1. a.

Then

$$\left\|u_{\Delta}\right\|_{C_{0}(I) }\leq C\|\mathbf{f}\|_{\max},$$
(55)

where C depends on the global quasi-uniformity h/h min with h min := min{h τ : τ ∈ Δ}. Let fC (I) for some 0 ≤ ≤ 4. Then

$$\|f-u_{\Delta}\| \leq Ch^{\ell}\left\|f^{(\ell)}\right\|.$$
(56)
2. b.

Let the constant of local quasi-uniformity be given by

$$\kappa:=\max_{1\leq i\leq N-1}\left\{\max\left\{\frac{h_{\tau_{i}}}{h_{\tau_{i+1}}},\frac{h_{\tau_{i+1}}}{h_{\tau_{i}}}\right\}\right\}$$
(57)

and assume κ 2 <2. Then

$$\left\| u_{\Delta}\right\|_{C^{0}(I)}\leq C_{\Delta}\|\mathbf{f}\|_{\max}\quad\text{ with }~C_{\Delta}\leq\frac{C}{2-\kappa^{2}},$$
(58)

where C only depends on κ. Let fC (I) for some 0 ≤ ≤ 4. Then

$$\left\| f-u_{\Delta}\right\| \leq\frac{C}{2-\kappa^{2}}h^{\ell}\left\|f^{(\ell)}\right\|.$$
(59)

### Proof

For $$k,p\in \mathbb {N}_{0}$$, let

$$S^{k,p}:=\left\{v\in C^{k}(I)\mid \forall\tau_{i},~ v|_{\tau_{i}}\in\mathbb{P}_{p}\right\}\quad\text{ and }\quad S_{0}^{k,p}:=\left\{v\in S^{k,p}:v(0)=v(1)=0\right\}.$$

For simplicity, we assume that N ≥ 4. We construct a function u auxS 4,9 such that

$$u_{\text{aux}}^{(k)}(t_{i})=f_{i,k},\qquad0\leq k\leq4,~0\leq i\leq N,$$

where, for 0 ≤ iN and 0 ≤ k ≤ 4, the values f i, k are divided differences

$$f_{i,k}:=\left\{ \begin{array}{ll} \left[t_{j-k/2},\ldots,t_{j+k/2}\right]f, & k\text{even},\\ \left[t_{j-\frac{k+1}{2}},\ldots,t_{j-1},t_{j+1},\ldots,t_{j+\frac{k+1}{2}}\right]f, & k\text{ odd} \end{array} \right.$$

which are centered at

$$j:=j_{i,k}:=\left\{ \begin{array}{ll} \left\lceil \frac{k}{2}\right\rceil,& i<\left\lceil \frac{k}{2}\right\rceil,\\ N-\left\lceil \frac{k}{2}\right\rceil,& i>N-\left\lceil \frac{k}{2}\right\rceil,\\ i, & \text{ otherwise}. \end{array} \right.$$
(60)

As usual for Hermite interpolation, we initialize the divided differences by

$$\left[\underset{(k+1)\times}{\underbrace{t_{\ell},\ldots,t_{\ell}}}\right]f:=f_{\ell,k}\quad\text{ for }~\ell=i-1,i~\text{ and }~0\leq k\leq4$$

and employ for the remaining differences the recursion

$$\left[\underset{m\text{-times}}{\underbrace{t_{i-1},\ldots t_{i-1}}},\underset{n\text{-times}}{\underbrace{t_{i},\ldots,t_{i}}}\right]f:=\frac{\left[\underset{(m-1) \text{-times}}{\underbrace{t_{i-1},{\ldots} t_{i-1}}},\underset{n\text{-times}}{\underbrace{t_{i},\ldots,t_{i}}}\right] f-\left[ \underset{m\text{-times}}{\underbrace{t_{i-1},{\ldots} t_{i-1}}},\underset{(n-1)\text{-times} }{\underbrace{t_{i},\ldots,t_{i}}}\right] f}{h_{i}}$$

for m ≥ 1 and n ≥ 1. On an interval τ = [t i−1, t i ], this leads to

$$u_{\text{aux}}|_{\tau_{i}}=\sum\limits_{k=0}^{4}f_{i-1,k}\omega_{i-1,k}+{\sum}_{k=0}^{4} \left( \left[\underset{5\times}{\underbrace{t_{i-1},\ldots,t_{i-1}}},\underset{(k+1) \times}{\underbrace{t_{i},\ldots,t_{i}}}\right]f\right)\omega_{i,k},$$

where, for 0 ≤ k ≤ 4,

$$\omega_{\ell,k}(t) :=\left\{ \begin{array}{ll} \left( t-t_{i-1}\right)^{k}, & \ell=i-1,\\ \left( t-t_{i-1}\right)^{5}\left( t-t_{i}\right)^{k}, & \ell=i. \end{array} \right.$$

Thus, we get for 0 ≤ m ≤ 4

$$\left|\omega_{\ell,k}^{(m)}(t)\right| \leq C_{1}\left\{ \begin{array}{ll} 0, & m>k\wedge\ell=i-1,\\ h_{\tau_{i}}^{k-m}, & m\leq k\wedge\ell=i-1,\\ h_{\tau_{i}}^{5+k-m}, & \ell=i. \end{array} \right.$$

We introduce the index neighborhood (cf. (60))

$$\iota_{i}:=\left\{ j_{i-1,4}-2,\ldots,j_{i-1,4}+2\right\}\cup\left\{j_{i,4}-2,\ldots,j_{i,4}+2\right\}$$

which contains those indices which are involved in the definition of $$\left [ \underset {m\text {-times}}{\underbrace {t_{i-1},\ldots t_{i-1}}},\underset {n\text {-times}}{\underbrace {t_{i},\ldots ,t_{i}}}\right ] f$$ for 0 ≤ m ≤ 4, 0 ≤ n ≤ 4 with (m, n)≠(0,0). We set

$$h_{i,\min}:=\min\{h_{n}:n\in\iota_{i}\}$$

and obtain

$$\left[\underset{m\text{-times}}{\underbrace{t_{i-1},\ldots t_{i-1}}},\underset{n\text{-times}}{\underbrace{t_{i},\ldots,t_{i}}}\right] f\leq C_{2}\frac{\left\|(f_{n,k})_{n\in\iota_{i}}\right\|_{\max}}{h_{i,\min}^{m+n-k-1}}\quad\text{ for }~0\leq k\leq m+n-1\leq4.$$

Thus, for 0 ≤ rm ≤ 4, it holds

$$\begin{array}{@{}rcl@{}} \left\|u_{\text{aux}}^{(m)}\right\|_{C^{0}(\tau_{i})}&\leq & \sum\limits_{s=m}^{4}\frac{\left\|(f_{n,r})_{n\in\iota_{i}}\right\|}{h_{i,\min}^{s-r}}h_{\tau_{i}}^{s-m}+\sum\limits_{s=0}^{4}\frac{\left\|(f_{n,r})_{n\in\iota_{i}}\right\|}{h_{i,\min}^{s+5-r}}h_{\tau_{i}}^{s+5-m},\\ &\leq & C_{1}C_{2}\left( \sum\limits_{s=m}^{4}\left\|(f_{n,r})_{n\in\iota_{i}}\right\|_{\max}\left( \frac{h_{\tau_{i}}}{h_{i,\min}}\right)^{s-r}h_{\tau_{i}}^{r-m}\right. \\ && \left. +\sum\limits_{s=0}^{4}\left\|(f_{n,r})_{n\in\iota_{i}}\right\|_{\max}\left( \frac{h_{\tau_{i}}}{h_{i,\min}}\right)^{5+s-r}h_{\tau_{i}}^{r-m}\right) \\ &\leq & C_{3}h_{\tau_{i}}^{r-m}\left\|(f_{n,r})_{n\in\iota_{i}}\right\|_{\max}, \end{array}$$
(61)

where C 3 only depends on the local quasi uniformity, i.e., on κ. This leads to

$$\|u_{\Delta}\|\leq \left\|u_{\text{aux}}\right\| + \left\| u_{\Delta}-u_{\text{aux}}\right\| \leq C_{3}\|\mathbf{f}\|_{\max}+\left\| u_{\Delta }-u_{\text{aux}}\right\|.$$

Proof of Case a. We employ [12,Theorem 2] and (61) to obtain

$$\left\|u_{\Delta}-u_{\text{aux}}\right\| \leq Ch^{4}\left\|u_{\text{aux}}^{(4)}\right\| \leq C\left( \frac{h}{h_{\min}}\right)^{4}\|\mathbf{f}\|_{\max}.$$
(62)

To prove (56), we assume fC (I) for some 0 ≤ ≤ 4. Then, well known properties of divided differences imply

$$\max_{1\leq i\leq N}\left\{h_{\tau_{i}}^{\ell-m}\left\|\left( f_{n,\ell}\right)_{n\in\iota_{i}}\right\|_{\max}\right\} \leq Ch^{\ell-m}\left\|f^{(\ell)}\right\|$$
(63)

and similarly as in (62) we get

$$\left\|u_{\Delta}-u_{\text{aux}}\right\| \leq Ch^{4}\left\|u_{\text{aux}}^{(4)}\right\| \leq Ch^{\ell}\left\|f^{(\ell)}\right\|,$$

where C depends on the global shape regularity h/h min.

Proof of Case b. From Corollary, we conclude that on an interval τ = [t i−1, t i ] it holds

$$\left\|u_{\Delta}-u_{\text{aux}}\right\|_{C^{0}(\tau)}\leq\frac{1}{8}h_{\tau}^{2}\left( \frac{h_{\tau}^{2}}{8}\left\|u_{\text{aux}}^{(4)}\right\| _{C^{0}(\tau)}+\max_{\ell\in\{i-1,i\}}\left\{\left| u_{\text{aux}}^{(2)}\left( t_{\ell}\right) -u_{\Delta}^{(2)}\left( t_{\ell}\right)\right|\right\}\right).$$
(64)

The first term in the right-hand side of (64) can be estimated by using (61) with m = 4

$$\left( \frac{h_{\tau}^{2}}{8}\right)^{2}\left\| u_{\text{aux}}^{(4)}\right\|_{C^{0}(\tau)}\leq C_{4}\left\|\left( f_{n}\right)_{n\in\iota_{i}}\right\|_{\max},$$
(65)

where C 4, again, only depends on the local quasi uniformity, i.e., on κ. Let ∈{1,…,N−1} be such that

$$h_{\ell}^{2}\left|d_{\ell}^{(2)}\right| =\left\|\mathbf{h}^{2}\mathbf{d}^{(2)}\right\|_{\max}$$

with

$$d_{i}^{(2)}:=u_{\text{aux}}^{(2)}\left( t_{i}\right) - u_{\Delta}^{(2)}\left( t_{i}\right),\quad \mathbf{h}^{2}\mathbf{d}^{(2)}:=\left( {h_{i}^{2}}d_{i}^{(2)}\right)_{i=1}^{N-1},\quad h_{i}:=\frac{h_{\tau_{i}}+h_{\tau_{i+1}}}{2}.$$

Then, according to (2), the differences $$d_{i}^{(2)}$$ satisfy the relation

$$\alpha_{\ell}d_{\ell-1}^{(2)}+2d_{\ell}^{(2)}+\left( 1-\alpha_{\ell}\right)d_{\ell+1}^{(2)}=r_{\ell}$$
(66)

with $$\alpha _{\ell }=\frac {h_{\tau _{\ell }}}{h_{\tau _{\ell }}+h_{\tau _{\ell +1}}}$$ and

$$r_{\ell}:=\alpha_{\ell}u_{\text{aux}}^{(2)}\left( t_{\ell-1}\right)+2u_{\text{aux}}^{(2)}\left( t_{\ell}\right) +\left( 1-\alpha_{\ell}\right)u_{\text{aux}}^{(2)}\left( t_{\ell+1}\right) -6\left[t_{\ell-1},t_{\ell},t_{\ell+1}\right] f.$$

Multiplying (66) by $$h_{\ell }^{2}$$ leads toFootnote 4

$$h_{\ell}^{2}r_{\ell} =\alpha_{\ell}\left( \frac{h_{\ell}}{h_{\ell-1}}\right)^{2}h_{\ell-1}^{2}d_{\ell-1}^{(2)}+2h_{\ell}^{2}d_{\ell}^{(2)}+\left( 1-\alpha_{\ell}\right) \left( \frac{h_{\ell}}{h_{\ell+1}}\right)^{2}h_{\ell+1}^{2}d_{\ell+1}^{(2)}\geq h_{\ell}^{2}d_{\ell}^{(2)}\left( 2-\kappa^{2}\right).$$

Hence

$$\left\|\mathbf{h}^{2}\mathbf{d}^{(2)}\right\|_{\max}\leq\frac{1}{2-\kappa^{2}}\left\| \mathbf{h}^{2}\mathbf{r}\right\|_{\max}.$$

From (2), we conclude that

$$\left| {h_{i}^{2}}r_{i}\right| \leq2{h_{i}^{4}}\left\|u_{\text{aux}}^{(4)}\right\|_{C^{0}\left( \omega_{i}\right)}\overset{(61)}{\leq}C_{5}\left\|\left( f_{n}\right)_{n\in\iota_{i}^{\star}}\right\|_{\max}$$

with

$$\omega_{i}:=\bigcup\{\tau\in{\Delta}\mid t_{i}\in\tau\}\quad\text{ and }\quad\iota_{i}^{\star}:=\bigcup_{k:t_{i}\in\tau_{k}}\iota_{k}.$$

Thus, the second term in (64) can be estimated by

$$\frac{1}{8}h_{\tau}^{2}\max_{\ell\in\{i-1,i\}}\left\{\left| u_{\text{aux}}^{(2)}\left( t_{\ell}\right)-u_{\Delta}^{(2)}\left( t_{\ell}\right)\right|\right\} \leq C_{6}\|\mathbf{f}\|_{\max}$$

and (58) follows.

To prove (59), we assume fC (I) for some 0 ≤ ≤ 4 and estimate next the first term in the right-hand side in (65) by using (61)

$$\left( \frac{h_{\tau}^{2}}{8}\right)^{2}\left\| u_{\text{aux}}^{(4)}\right\|_{C^{0}(\tau)}\leq C_{7}h^{\ell}\left\| f^{(\ell) }\right\|.$$

For the second term in (64), we first observe that

$$\max_{1\leq i\leq N-1}\left| {h_{i}^{2}}r_{i}\right| \leq2\max_{1\leq i\leq N-1}{h_{i}^{4}}\left\|u_{\text{aux}}^{(4)}\right\|_{C^{0}\left( \omega_{i}\right)}\overset{(61)}{\leq}Ch^{\ell}\left\| f^{(\ell) }\right\|$$

holds so that the second term in (64) can be estimated by

$$\frac{1}{8}h_{\tau}^{2}\max_{\ell\in\{i-1,i\}}\left\{\left| u_{\text{aux}}^{(2)}\left( t_{\ell}\right) -u_{\Delta}^{(2)}\left( t_{\ell}\right) \right|\right\} \leq Ch^{\ell}\left\| f^{(\ell)}\right\|,$$

where C only depends on the local quasi-uniformity of the mesh and (58) follows. □

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