diff --git a/wpilibc/shared/include/Filters/LinearDigitalFilter.h b/wpilibc/shared/include/Filters/LinearDigitalFilter.h
index f00aefb9b0..325a1bc629 100644
--- a/wpilibc/shared/include/Filters/LinearDigitalFilter.h
+++ b/wpilibc/shared/include/Filters/LinearDigitalFilter.h
@@ -18,17 +18,17 @@
  * filters are supported. Static factory methods are provided to create commonly
  * used types of filters.
  *
- * Filters are of the form:
- *  y[n] = (b0*x[n] + b1*x[n-1] + ... + bP*x[n-P]) - (a0*y[n-1] + a2*y[n-2] +
- * ... + aQ*y[n-Q])
+ * Filters are of the form:<br>
+ *  y[n] = (b0 * x[n] + b1 * x[n-1] + … + bP * x[n-P]) -
+ *         (a0 * y[n-1] + a2 * y[n-2] + … + aQ * y[n-Q])
  *
- * Where:
- *  y[n] is the output at time "n"
- *  x[n] is the input at time "n"
- *  y[n-1] is the output from the LAST time step ("n-1")
- *  x[n-1] is the input from the LAST time step ("n-1")
- *  b0...bP are the "feedforward" (FIR) gains
- *  a0...aQ are the "feedback" (IIR) gains
+ * Where:<br>
+ *  y[n] is the output at time "n"<br>
+ *  x[n] is the input at time "n"<br>
+ *  y[n-1] is the output from the LAST time step ("n-1")<br>
+ *  x[n-1] is the input from the LAST time step ("n-1")<br>
+ *  b0 … bP are the "feedforward" (FIR) gains<br>
+ *  a0 … aQ are the "feedback" (IIR) gains<br>
  * IMPORTANT! Note the "-" sign in front of the feedback term! This is a common
  *            convention in signal processing.
  *
@@ -48,10 +48,10 @@
  *    electrical or mechanical components
  *  - If you use clever gains, you can make a PID controller out of this class!
  *
- * For more on filters, I highly recommend the following articles:
- *  http://en.wikipedia.org/wiki/Linear_filter
- *  http://en.wikipedia.org/wiki/Iir_filter
- *  http://en.wikipedia.org/wiki/Fir_filter
+ * For more on filters, I highly recommend the following articles:<br>
+ *  http://en.wikipedia.org/wiki/Linear_filter<br>
+ *  http://en.wikipedia.org/wiki/Iir_filter<br>
+ *  http://en.wikipedia.org/wiki/Fir_filter<br>
  *
  * Note 1: PIDGet() should be called by the user on a known, regular period.
  * You can set up a Notifier to do this (look at the WPILib PIDController
diff --git a/wpilibc/shared/src/Filters/LinearDigitalFilter.cpp b/wpilibc/shared/src/Filters/LinearDigitalFilter.cpp
index e8a24335c9..2a899c468f 100644
--- a/wpilibc/shared/src/Filters/LinearDigitalFilter.cpp
+++ b/wpilibc/shared/src/Filters/LinearDigitalFilter.cpp
@@ -75,11 +75,11 @@ LinearDigitalFilter::LinearDigitalFilter(std::shared_ptr<PIDSource> source,
       m_outputGains(fbGains) {}
 
 /**
- * Creates a one-pole IIR low-pass filter of the form:
- *   y[n] = (1-gain)*x[n] + gain*y[n-1]
- * where gain = e^(-dt / T), T is the time constant in seconds
+ * Creates a one-pole IIR low-pass filter of the form:<br>
+ *   y[n] = (1 - gain) * x[n] + gain * y[n-1]<br>
+ * where gain = e<sup>-dt / T</sup>, T is the time constant in seconds
  *
- * This filter is stable for time constants greater than zero
+ * This filter is stable for time constants greater than zero.
  *
  * @param source       The PIDSource object that is used to get values
  * @param timeConstant The discrete-time time constant in seconds
@@ -92,11 +92,11 @@ LinearDigitalFilter LinearDigitalFilter::SinglePoleIIR(
 }
 
 /**
- * Creates a first-order high-pass filter of the form:
- *   y[n] = gain*x[n] + (-gain)*x[n-1] + gain*y[n-1]
- * where gain = e^(-dt / T), T is the time constant in seconds
+ * Creates a first-order high-pass filter of the form:<br>
+ *   y[n] = gain * x[n] + (-gain) * x[n-1] + gain * y[n-1]<br>
+ * where gain = e<sup>-dt / T</sup>, T is the time constant in seconds
  *
- * This filter is stable for time constants greater than zero
+ * This filter is stable for time constants greater than zero.
  *
  * @param source       The PIDSource object that is used to get values
  * @param timeConstant The discrete-time time constant in seconds
@@ -109,8 +109,8 @@ LinearDigitalFilter LinearDigitalFilter::HighPass(
 }
 
 /**
- * Creates a K-tap FIR moving average filter of the form:
- *   y[n] = 1/k * (x[k] + x[k-1] + ... + x[0])
+ * Creates a K-tap FIR moving average filter of the form:<br>
+ *   y[n] = 1/k * (x[k] + x[k-1] + … + x[0])
  *
  * This filter is always stable.
  *