Functions of Bounded Variation

This scene measures the total distance a function wiggles. If that sum stays under a finite ceiling, the function has bounded variation.

Start and finish alone are not enough. Every up and down in between must be added. Monotone functions pass since they wiggle one way only. Endless trembling makes the sum explode.

For example, a πŸš— car driving up and down has bounded variation while its total mileage stays definite. Trembling in place forever would pile the distance up without end.

Vab(f)=sup⁑Pβˆ‘i=1n∣f(xi)βˆ’f(xiβˆ’1)∣<∞V_a^b(f) = \sup_P \sum_{i=1}^{n} \lvert f(x_i) - f(x_{i-1})\rvert < \infty
f=gβˆ’h,g,hΒ increasingΒ (Jordan)f = g - h, \quad g, h\ \text{increasing (Jordan)}

Part of these learning paths

Examples & Exercises

Show that every monotone function ff on [a,b][a, b] is of bounded variation with Vab(f)=∣f(b)βˆ’f(a)∣V_a^b(f) = |f(b) - f(a)|.

Vab(f):=sup⁑Pβˆ‘i=1m∣f(xi)βˆ’f(xiβˆ’1)∣V_a^b(f) := \sup_P \sum_{i=1}^{m} \bigl|f(x_i) - f(x_{i-1})\bigr|
βˆ‘i=1m∣f(xi)βˆ’f(xiβˆ’1)∣=βˆ‘i=1m(f(xi)βˆ’f(xiβˆ’1))=f(b)βˆ’f(a)(fΒ increasing)\sum_{i=1}^{m} \bigl|f(x_i) - f(x_{i-1})\bigr| = \sum_{i=1}^{m} \bigl(f(x_i) - f(x_{i-1})\bigr) = f(b) - f(a) \quad (f \text{ increasing})
n=40n = 40: f(x)=sin⁑(2Ο€x)f(x) = \sin(2\pi x) is not monotone, yet V40β‰ˆ3.9968V_{40} \approx 3.9968 β€” when ff is monotone, the sum telescopes on every partition, fixing the variation at ∣f(b)βˆ’f(a)∣|f(b) - f(a)|.
Show proof
  1. Let ff be increasing on [a,b][a, b] and take any partition P={x0<x1<β‹―<xm}P = \{x_0 < x_1 < \dots < x_m\} ([x0,xm]=[a,b][x_0, x_m] = [a, b]). Monotonicity gives f(xi)βˆ’f(xiβˆ’1)β‰₯0f(x_i) - f(x_{i-1}) \ge 0 on each subinterval, so the absolute values unwrap: βˆ‘i=1m∣f(xi)βˆ’f(xiβˆ’1)∣=βˆ‘i=1m(f(xi)βˆ’f(xiβˆ’1))\sum_{i=1}^{m}|f(x_i) - f(x_{i-1})| = \sum_{i=1}^{m}(f(x_i) - f(x_{i-1})), which telescopes to f(b)βˆ’f(a)f(b) - f(a).

  2. The decreasing case is the same: f(xi)βˆ’f(xiβˆ’1)≀0f(x_i) - f(x_{i-1}) \le 0, so ∣f(xi)βˆ’f(xiβˆ’1)∣=f(xiβˆ’1)βˆ’f(xi)|f(x_i) - f(x_{i-1})| = f(x_{i-1}) - f(x_i) and the sum is f(a)βˆ’f(b)=∣f(b)βˆ’f(a)∣f(a) - f(b) = |f(b) - f(a)|. Every partition of a monotone ff gives the same variation ∣f(b)βˆ’f(a)∣|f(b) - f(a)|.

  3. Hence the supremum over partitions is ∣f(b)βˆ’f(a)∣<∞|f(b) - f(a)| < \infty, i.e. Vab(f)=∣f(b)βˆ’f(a)∣V_a^b(f) = |f(b) - f(a)|: monotone functions are of bounded variation. The Cantor function (see the limits chapter) is increasing on [0,1][0, 1] with c(0)=0c(0) = 0, c(1)=1c(1) = 1, so V01(c)=1V_0^1(c) = 1.

Jordan decomposition: ff is of bounded variation on [a,b][a, b] if and only if f=gβˆ’hf = g - h with g,hg, h increasing on [a,b][a, b].

Hint: set v(x):=Vax(f)v(x) := V_a^x(f).

v(x):=Vax(f),f=v+f2βˆ’vβˆ’f2v(x) := V_a^x(f), \qquad f = \frac{v + f}{2} - \frac{v - f}{2}
Vxy(f)β‰₯Β±(f(y)βˆ’f(x))(a≀x<y≀b)V_x^y(f) \ge \pm\bigl(f(y) - f(x)\bigr) \quad (a \le x < y \le b)
n=80n = 80: V80β‰ˆ3.9992V_{80} \approx 3.9992 β€” the cumulative variation v(x)=V0x(sin⁑2π ⋅)v(x) = V_0^x(\sin 2\pi\,\cdot) is itself increasing, so f=v+f2βˆ’vβˆ’f2f = \frac{v+f}{2} - \frac{v-f}{2} splits ff into a difference of two increasing functions.
Show proof
  1. Assume ff is of bounded variation on [a,b][a, b] and set v(x):=Vax(f)v(x) := V_a^x(f) for a≀x≀ba \le x \le b. Variation is additive over adjacent intervals, Vay(f)=Vax(f)+Vxy(f)V_a^y(f) = V_a^x(f) + V_x^y(f) for a≀x<y≀ba \le x < y \le b, so v(y)βˆ’v(x)=Vxy(f)β‰₯0v(y) - v(x) = V_x^y(f) \ge 0: vv is increasing.

  2. The key inequality: the trivial partition {x,y}\{x, y\} of [x,y][x, y] is one of the partitions in the supremum, so Vxy(f)β‰₯∣f(y)βˆ’f(x)∣β‰₯Β±(f(y)βˆ’f(x))V_x^y(f) \ge |f(y) - f(x)| \ge \pm(f(y) - f(x)). Hence v(y)βˆ’v(x)β‰₯f(y)βˆ’f(x)v(y) - v(x) \ge f(y) - f(x) and also v(y)βˆ’v(x)β‰₯βˆ’(f(y)βˆ’f(x))v(y) - v(x) \ge -(f(y) - f(x)).

  3. Set g:=v+f2g := \frac{v + f}{2} and h:=vβˆ’f2h := \frac{v - f}{2}. Then g(y)βˆ’g(x)=12((v(y)βˆ’v(x))+(f(y)βˆ’f(x)))β‰₯0g(y) - g(x) = \frac{1}{2}\bigl((v(y) - v(x)) + (f(y) - f(x))\bigr) \ge 0 and h(y)βˆ’h(x)=12((v(y)βˆ’v(x))βˆ’(f(y)βˆ’f(x)))β‰₯0h(y) - h(x) = \frac{1}{2}\bigl((v(y) - v(x)) - (f(y) - f(x))\bigr) \ge 0, so gg and hh are both increasing, and gβˆ’h=fg - h = f.

  4. Conversely, if f=gβˆ’hf = g - h with g,hg, h increasing, then by problem 1 both are of bounded variation, and the triangle inequality gives ∣f(xi)βˆ’f(xiβˆ’1)βˆ£β‰€βˆ£g-diff∣+∣h-diff∣|f(x_i) - f(x_{i-1})| \le |g\text{-diff}| + |h\text{-diff}|, so VP(f)≀VP(g)+VP(h)=(g(b)βˆ’g(a))+(h(b)βˆ’h(a))<∞V_P(f) \le V_P(g) + V_P(h) = (g(b) - g(a)) + (h(b) - h(a)) < \infty: ff is of bounded variation. So ff is BV β€…β€ŠβŸΊβ€…β€Š\iff f=gβˆ’hf = g - h (unique up to an additive constant).

Show that ff with f(0)=0f(0) = 0 and f(x)=xsin⁑(1/x)f(x) = x\sin(1/x) for x>0x > 0 is NOT of bounded variation on [0,1][0, 1].

uk=12Ο€k+Ο€/2,β€…β€Šf(uk)=uk,vk=12Ο€k+3Ο€/2,β€…β€Šf(vk)=βˆ’vku_k = \frac{1}{2\pi k + \pi/2},\; f(u_k) = u_k, \qquad v_k = \frac{1}{2\pi k + 3\pi/2},\; f(v_k) = -v_k
V(f)β‰₯βˆ‘k=1N(uk+vk)β‰₯βˆ‘k=1N12Ο€k=HN2Ο€βŸΆβˆžV(f) \ge \sum_{k=1}^{N}(u_k + v_k) \ge \sum_{k=1}^{N}\frac{1}{2\pi k} = \frac{H_N}{2\pi} \longrightarrow \infty
n=200n = 200: V200β‰ˆ2.1388V_{200} \approx 2.1388 β€” already past the proof's lower bound βˆ‘k=1200(uk+vk)β‰ˆ1.6849>1\sum_{k=1}^{200}(u_k + v_k) \approx 1.6849 > 1, and since HN/(2Ο€)β†’βˆžH_N/(2\pi) \to \infty the variation admits no finite upper bound.
Show proof
  1. Take uk=12Ο€k+Ο€/2u_k = \frac{1}{2\pi k + \pi/2} where sin⁑(1/x)=1\sin(1/x) = 1 (so f(uk)=ukf(u_k) = u_k) and vk=12Ο€k+3Ο€/2v_k = \frac{1}{2\pi k + 3\pi/2} where sin⁑(1/x)=βˆ’1\sin(1/x) = -1 (so f(vk)=βˆ’vkf(v_k) = -v_k). Comparing denominators, 0<vk<uk<10 < v_k < u_k < 1, and uk+1=12Ο€k+5Ο€/2<vku_{k+1} = \frac{1}{2\pi k + 5\pi/2} < v_k, so the points line up as 0<vN<uN<β‹―<v1<u1<10 < v_N < u_N < \dots < v_1 < u_1 < 1.

  2. Take the partition PN={0,vN,uN,…,v1,u1,1}P_N = \{0, v_N, u_N, \dots, v_1, u_1, 1\}.

    The contributions from [0,vN][0, v_N] and [u1,1][u_1, 1] are nonnegative, so dropping them only lowers the sum; on each pair (vk,uk)(v_k, u_k) we get ∣f(uk)βˆ’f(vk)∣=∣ukβˆ’(βˆ’vk)∣=uk+vk|f(u_k) - f(v_k)| = |u_k - (-v_k)| = u_k + v_k.

    Hence VPN(f)β‰₯βˆ‘k=1N(uk+vk)V_{P_N}(f) \ge \sum_{k=1}^{N}(u_k + v_k).

  3. Now uk+vkβ‰₯2vk=22Ο€k+3Ο€/2β‰₯12Ο€ku_k + v_k \ge 2v_k = \frac{2}{2\pi k + 3\pi/2} \ge \frac{1}{2\pi k}: the last inequality is equivalent to 4Ο€kβ‰₯2Ο€k+3Ο€/24\pi k \ge 2\pi k + 3\pi/2, i.e. 4kβ‰₯34k \ge 3 for kβ‰₯1k \ge 1. Therefore VPN(f)β‰₯βˆ‘k=1N12Ο€k=HN2Ο€β†’βˆžV_{P_N}(f) \ge \sum_{k=1}^{N} \frac{1}{2\pi k} = \frac{H_N}{2\pi} \to \infty as Nβ†’βˆžN \to \infty.

  4. Since the partition variations diverge, sup⁑PVP(f)=∞\sup_P V_P(f) = \infty: ff is not of bounded variation on [0,1][0, 1]. Numerical check: u1=12.5Ο€β‰ˆ0.12732u_1 = \frac{1}{2.5\pi} \approx 0.12732, v1=13.5Ο€β‰ˆ0.09095v_1 = \frac{1}{3.5\pi} \approx 0.09095, βˆ‘k=1200(uk+vk)β‰ˆ1.6849>1\sum_{k=1}^{200}(u_k + v_k) \approx 1.6849 > 1 β€” the scene's V200β‰ˆ2.1388V_{200} \approx 2.1388 already exceeds this lower bound. (Contrast: x2sin⁑(1/x)x^2\sin(1/x) IS of bounded variation, with V≀3V \le 3, since ∫01∣fβ€²βˆ£β‰€2\int_0^1 |f'| \le 2.)

11. Integration