minor edit to emm doc

Author: Alexander Ororbia

ngclearn/utils/density/exponentialMixture.py

@@ -61,11 +61,16 @@ def _sample_component(dkey, n_samples, rate): ## samples a component (of mixture
 
 class ExponentialMixture(Mixture): ## Exponential mixture model (mixture-of-exponentials)
     """
-    Implements a exponential mixture model (EMM) -- or mixture of exponentials (MoExp). Adaptation of parameters is
+    Implements an exponential mixture model (EMM) -- or mixture of exponentials (MoExp). Adaptation of parameters is
     conducted via the Expectation-Maximization (EM) learning algorithm. Note that this exponential mixture assumes that
     each component is a factorizable mutlivariate exponential distribution. (A Categorical distribution is assumed over
     the latent variables).
 
+    The exponential distribution of each component (dimension `d`) is assumed to be: 
+
+    | pdf(x_d; lmbda_d) = lmbda_d * exp(-lmbda_d x_d) for x >= 0, else 0 for x < 0; 
+    | where lbmda is the rate parameter vector
+
     Args:
         K: the number of components/latent variables within this EMM