diff --git a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
index 041b9e7..b2de716 100644
--- a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
@@ -50,12 +50,12 @@
      * @param[in, out] input   Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
      *                         3 lower dimensions represent a single input with dimensions [width, height, FM].
      *                         The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+     * @param[out]     output  Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
      * @param[in]      mean    Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
      * @param[in]      var     Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
-     * @param[in]      gamma   Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
      * @param[in]      beta    Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+     * @param[in]      gamma   Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
      * @param[in]      epsilon Small value to avoid division with zero.
-     * @param[out]     output  Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
      */
     void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon);