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Sequence - Part 6


Today we will learn about difference operator and use it to prove a fundamental theorem for linear recurrence equations.
A fundamental theorem for linear recurrence equations. Suppose that the characteristic equation can be factored as f(x) = a_k x^k + a_{k-1} x^{k-1} + \dots + a_0 = (x - z)^j (b_s x^s + b_{s-1} x^{s-1} + \dots + b_0) and f_n = p(n)~z^n, where p(n) is a polynomial of degree less than j. Then the sequence f_n satisfies the recurrence equation 
a_k f_{n} + a_{k-1} f_{n-1} + \dots + a_1 f_{n-k+1} + a_0 f_{n-k} = 0.


Difference operator

First, let us learn about difference operator. The (forward) difference operator \Delta is defined simply as \Delta (P(x)) = P(x+1) - P(x). Here are some examples
  • If P(x) = 5 then \Delta(P(x))=5-5=0;
  • If P(x) = x then \Delta(P(x))= (x+1)-x = 1;
  • If P(x) = x^2 then \Delta(P(x))= (x+1)^2 - x^2 = 2x + 1;
  • If P(x) = 3 x^2 + 2x + 1 then \Delta(P(x))= [3 (x+1)^2 + 2(x+1) + 1]  - [3 x^2 + 2x + 1] = 6x + 5;
  • If P(x) = \frac{1}{x} then \Delta(P(x))= \frac{1}{x+1}  - \frac{1}{x} = - \frac{1}{x(x+1)}.
  • If P(x) = 2^{x} then \Delta(P(x))= 2^{x+1}  - 2^{x} = 2^x.
  • If P(x) = 3^{x} then \Delta(P(x))= 3^{x+1}  - 3^{x} = 2 \times 3^x.


Clearly, the difference operator has the following properties
  • Additivity: \Delta(u(x) + v(x)) = \Delta(u(x)) + \Delta(v(x));
  • Homogeneity: for any constant a, \Delta(a ~P(x)) = a ~\Delta(P(x)).




Higher-order difference

We can repeat the application of difference operator to create differences of higher orders as follows.
  • Let us start with the usual difference operator (it is called the difference of order 1) \Delta(P(x)) = P(x+1) - P(x).
  • Next, we apply the difference operator to \Delta(P(x)), the result is the difference of order 2, we will use the following notation \Delta^2(P(x)) = \Delta(\Delta(P(x))) = \Delta(P(x+1) - P(x)). Thus, \Delta^2(P(x)) = [P(x+2) - P(x+1)] - [P(x+1) - P(x)] = P(x+2) - 2 P(x+1) + P(x).
  • Again, the difference of order 3 is \Delta^3(P(x)) = P(x+3) - 3 P(x+2) + 3 P(x+1) - P(x).

Have you noticed any pattern yet? If you haven't, then keep calculating the differences of order 4, order 5 -- \Delta^4(P(x)), \Delta^5(P(x)) -- you will surely recognize the pattern.

The pattern is that the coefficients in the formula are the numbers in the Pascal triangle!
We can show that formula for the difference of order j is \Delta^j(P(x)) = P(x+j) - {j \choose {j-1}} P(x+j-1) + {j \choose {j-2}} P(x+j-2) - \dots + (-1)^{j-1} {j \choose 1} P(x+1) + (-1)^j P(x).
This is a very important formula that we will use in our later proof of the fundamental theorem for linear recurrence equations, so we will restate it

Formula for higher-order differences. The difference of order j of P(x) is \Delta^j(P(x)) = \sum_{v=0}^{j} (-1)^{j-v} {j \choose v} P(x + v).


Difference of polynomials

Let us now consider the application of difference operator to polynomials. A very important fact is that:
  • For any n > 0, if we apply the difference operator to a polynomial of degree n then we will obtain a polynomial of degree n-1.
Thus,
  • Difference of order n of a polynomial of degree n is a constant.
  • Difference of order n+1 of a polynomial of degree n is equal to 0.

On this blog, we have used these facts to prove Wilson's Theorem.

Let us pick an example, a polynomial of degree 3, P(x) = 2 x^3 + x^2 + 3 x + 5, and calculate its differences
  • We start with the difference of order 1 \Delta(P(x)) = [2(x+1)^3 + (x+1)^2 + 3(x+1) + 5] - [2 x^3 + x^2 + 3 x + 5] =2[(x+1)^3 - x^3] + [(x+1)^2 - x^2] + 3[(x+1)-x] =2[3 x^2 + 3x + 1] + [2x+1] + 3 =6 x^2 + 8x + 6, So the difference of order 1 of 2 x^3 + x^2 + 3 x + 5 is a polynomial of degree 2.
  • Next, the difference of order 2 \Delta^2(P(x)) = [6 (x+1)^2 + 8 (x+1) + 6] - [6 x^2 + 8x + 6] = 6 [(x+1)^2 - x^2] + 8 [(x+1) -x] = 6 [2x+1] + 8 = 12 x + 14 So the difference of order 2 of 2 x^3 + x^2 + 3 x + 5 is a polynomial of degree 1.
  • The difference of order 3 \Delta^3(P(x)) = [12 (x+1) + 14] - [12x + 14] = 12 The difference of order 3 of 2 x^3 + x^2 + 3 x + 5 is a constant.
  • Finally, the difference of order 4 of 2 x^3 + x^2 + 3 x + 5 is zero \Delta^4(P(x)) = 12 - 12 = 0. 
  • Clearly, each time we apply the difference operation, the degree of the polynomial decreases and finally, it becomes 0.




Proof of the fundamental theorem

A fundamental theorem for linear recurrence equations. Suppose that the characteristic equation can be factored as f(x) = a_k x^k + a_{k-1} x^{k-1} + \dots + a_0 = (x - z)^j (b_s x^s + b_{s-1} x^{s-1} + \dots + b_0) and f_n = p(n)~z^n, where p(n) is a polynomial of degree less than j. Then the sequence f_n satisfies the recurrence equation 
a_k f_{n} + a_{k-1} f_{n-1} + \dots + a_1 f_{n-k+1} + a_0 f_{n-k} = 0.

First, we will express each a_i in terms of the b_i. We have f(x) = \sum_{v=0}^{j}{(-1)^{j-v} {j \choose v} z^{j-v} x^v} \sum_{u=0}^{s}{b_u x^u} = \sum_{u=0}^{s} \sum_{v=0}^{j} (-1)^{j-v} {j \choose v} b_u z^{j-v} x^{u+v}

Therefore, we obtain a_w = \sum_{0 \leq u \leq s, ~0 \leq v \leq j, ~u+v=w} (-1)^{j-v} {j \choose v} b_u z^{j-v}

Now, let us substitute the above formula of a_i and f_i = p(i)~z^i into the recurrence equation. We have \sum_{w=0}^{k} a_w f_{n-k+w} = \sum_{w=0}^{k} a_w  p(n-k+w) z^{n-k+w}= z^{n-k}  \sum_{w=0}^{k} a_w  z^w p(n-k+w) =z^{n-k}  \sum_{w=0}^{k}  \sum_{0 \leq u \leq s, ~0 \leq v \leq j, ~u+v=w} (-1)^{j-v} {j \choose v} b_u z^{j-v} z^w p(n-k+w) =z^{n-k}  \sum_{w=0}^{k}  \sum_{0 \leq u \leq s, ~0 \leq v \leq j, ~u+v=w} (-1)^{j-v} {j \choose v} b_u z^{j+u}  p(n-k+w) =z^{n-k} \sum_{u=0}^{s} b_u z^{j+u} \sum_{v=0}^{j} (-1)^{j-v} {j \choose v} p(n-k+u+v).

By the formula of higher-order difference that we have learned above, we have \sum_{w=0}^{k} a_w f_{n-k+w} = z^{n-k} \sum_{u=0}^{s} b_u z^{j+u} \Delta^{j}(p(n-k+u)).


Since p(n) is a polynomial of degree less than j, for any value of u, p(n-k+u) is also a polynomial of variable n of degree less than j. Therefore, the difference of order j of p(n-k+u) must be terminated, i.e. \Delta^{j}(p(n-k+u)) = 0.

It follows that \sum_{w=0}^{k} a_w f_{n-k+w} = 0, this is the required recurrence equation and the proof is completed.



The above theorem is a fundamental theorem for solving linear recurrence equations. Indeed,
  • if the characteristic equation has a root x=z_1 of multiplicity j_1, then by the theorem, for any polynomial p_1(n) of degree less than j_1, the sequence \{p_1(n) z_1^n\} satisfies the recurrence equation;
  • if the characteristic equation has a root x=z_2 of multiplicity j_2, then by the theorem, for any polynomial p_2(n) of degree less than j_2, the sequence \{p_2(n) z_2^n\} satisfies the recurrence equation;...
  • if the characteristic equation has a root x=z_t of multiplicity j_t, then by the theorem, for any polynomial p_t(n) of degree less than j_t, the sequence \{p_t(n) z_t^n\} satisfies the recurrence equation;
  • thus, if we add all these sequences, we will have a sequence of the form f_n = p_1(n) z_1^n + p_2(n) z_2^n + \dots + p_t(n) z_t^n, this sequence also satisfies the recurrence equation. This is exactly the formula that we used in previous posts to solve recurrence equations.

Example: suppose we want to find a general formula for the sequence f_0=1, ~f_1 = 7, ~f_2= 32, ~f_n = 8 f_{n-1} - 21 f_{n-2} + 18 f_{n-3}. From the recurrence equation f_n = 8 f_{n-1} - 21 f_{n-2} + 18 f_{n-3} we solve the characteristic equation x^3 - 8 x^2 + 21 x - 18 = (x-2)(x-3)^2= 0. The fundamental theorem asserts that sequence of the form f_n = p_1(n) ~2^n + p_2(n) ~3^n, where p_1(n) is a polynomial of degree less than 1 and p_2(n) is a polynomial of degree less than 2, will satisfy the recurrence equation. We let p_1(n) = a, ~~~ p_2(n) = b + c ~n. Then f_n = a ~ 2^n + (b + c~n)~ 3^n. From the initial condition: f_0=1, f_1=7, f_2=32, we establish a system of equations  f_0 = a + b = 1, f_1 = 2 a + 3 b + 3 c = 7, f_2 = 4 a + 9 b + 18 c = 32. Solving this system of equations we obtain a = -1, b=2 and c = 1. Therefore, f_n = (2 + n) ~3^n - 2^n.


Let us end this post here with a review of the method of solving linear recurrence equations.

Suppose we have a sequence \{f_n\} that satisfies the recurrence equation a_k f_{n} + a_{k-1} f_{n-1} + a_{k-2} f_{n-2} + \dots + a_0 f_{n-k}=0 with some initial conditions on the values of f_0, f_1, \dots, f_{k-1}, we follow the following steps to determine a general formula for the sequence.

Step 1. Solve the recurrence equation.
Form the characteristic equation a_k x^k + a_{k-1} x^{k-1} + \dots + a_1 x + a_0=0 and determine its roots
a_k x^k + a_{k-1} x^{k-1} + \dots + a_1 x + a_0=a_k(x - z_1)^{j_1} (x - z_2)^{j_2} \dots (x - z_t)^{j_t}.
Suppose the characteristic equation has t roots z_1, \dots, z_t, where z_1 is a root of multiplicity j_1, z_2 is a root of multiplicity j_2, etc... Then for any polynomial p_1(n), ..., p_t(n) of degree less than j_1, ..., j_t, respectively, the sequence f_n = p_1(n)~ z_1^n + p_2(n) ~ z_2^n + \dots + p_t(n) ~z_t^n satisfies the recurrence equation a_k f_{n} + a_{k-1} f_{n-1} + a_{k-2} f_{n-2} + \dots + a_0 f_{n-k}=0. 
Step 2. Solve the initial condition.
Substituting the values of f_0, f_1, \dots, f_{k-1} into the formula of f_n to form a system of equations and solve this system of equations to derive a general formula for f_n.

We make a remark that if j_1 = \dots = j_t=1, i.e. the characteristic equation only has single roots as a_k x^k + a_{k-1} x^{k-1} + \dots + a_1 x + a_0=a_k(x - z_1) (x - z_2) \dots (x - z_k), then the polynomials p_1(n),..., p_k(n) have degree less than 1, that means they are equal to constants, so we can write p_i(n) = \alpha_i and we have the formula f_n = \alpha_1 ~ z_1^n + \alpha_2 ~ z_2^n+ \dots + \alpha_k ~ z_k^n.



Let us stop here for now. As we have proved the fundamental theorem for linear recurrence equations, now is a good time to go back to the first post of the series and read all the posts again.

Hope to see you again in the next post.






Homework.


1. Use mathematical induction to prove the formula for higher-order difference \Delta^j(P(x)) = \sum_{v=0}^{j} (-1)^{j-v} {j \choose v} P(x + v).

2. Prove the following important facts about difference of polynomials:
  • For any n > 0, if we apply the difference operator to a polynomial of degree n then we will obtain a polynomial of degree n-1.
  • Difference of order n of a polynomial of degree n is a constant.
  • Difference of order n+1 of a polynomial of degree n is equal to 0.

3. Calculate \Delta(P(x)) for the following cases:
  • P(x) = a^x
  • P(x) = x^n
  • P(x) = x(x+1)
  • P(x) = x(x+1)(x+2)
  • P(x) = 1/[x(x+1)]
  • P(x) = 1/[x(x+1)(x+2)]
  • P(x) = F_x the Fibonacci number

4. Determine the following summations 1 \times 2 + 2 \times 3 + \dots + n(n+1) \frac{1}{1 \times 2} + \frac{1}{2 \times 3} + \dots + \frac{1}{n(n+1)}
Generalize these results.

5. Prove the following formula for difference of a product
\Delta(u(x) v(x)) = \Delta(u(x)) ~v(x) + u(x+1) ~\Delta(v(x)).