diff --git a/arm_compute/core/NEON/wrapper/traits.h b/arm_compute/core/NEON/wrapper/traits.h
index 0dbd90d..cc22597 100644
--- a/arm_compute/core/NEON/wrapper/traits.h
+++ b/arm_compute/core/NEON/wrapper/traits.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -44,27 +44,27 @@
 template <typename T, int S> struct neon_vector;
 // Specializations
 #ifndef DOXYGEN_SKIP_THIS
-template <> struct neon_vector<uint8_t, 8>{ using type = uint8x8_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<int8_t, 8>{ using type = int8x8_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<uint8_t, 16>{ using type = uint8x16_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<int8_t, 16>{ using type = int8x16_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<uint16_t, 4>{ using type = uint16x4_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<int16_t, 4>{ using type = int16x4_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<uint16_t, 8>{ using type = uint16x8_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<int16_t, 8>{ using type = int16x8_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<uint32_t, 2>{ using type = uint32x2_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<int32_t, 2>{ using type = int32x2_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<uint32_t, 4>{ using type = uint32x4_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<int32_t, 4>{ using type = int32x4_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<uint64_t, 1>{ using type = uint64x1_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<int64_t, 1>{ using type = int64x1_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<uint64_t, 2>{ using type = uint64x2_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<int64_t, 2>{ using type = int64x2_t; using tag_type = vector_128_tag; };
-template <> struct neon_vector<float_t, 2>{ using type = float32x2_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<float_t, 4>{ using type = float32x4_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<uint8_t, 8>{ using scalar_type = uint8_t; using type = uint8x8_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<int8_t, 8>{ using scalar_type = int8_t; using type = int8x8_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<uint8_t, 16>{ using scalar_type = uint8_t; using type = uint8x16_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<int8_t, 16>{ using scalar_type = int8_t; using type = int8x16_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<uint16_t, 4>{ using scalar_type = uint16_t; using type = uint16x4_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<int16_t, 4>{ using scalar_type = int16_t; using type = int16x4_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<uint16_t, 8>{ using scalar_type = uint16_t; using type = uint16x8_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<int16_t, 8>{ using scalar_type = int16_t; using type = int16x8_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<uint32_t, 2>{ using scalar_type = uint32_t; using type = uint32x2_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<int32_t, 2>{ using scalar_type = int32_t; using type = int32x2_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<uint32_t, 4>{ using scalar_type = uint32_t; using type = uint32x4_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<int32_t, 4>{ using scalar_type = int32_t; using type = int32x4_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<uint64_t, 1>{ using scalar_type = uint64_t;using type = uint64x1_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<int64_t, 1>{ using scalar_type = int64_t; using type = int64x1_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<uint64_t, 2>{ using scalar_type = uint64_t; using type = uint64x2_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<int64_t, 2>{ using scalar_type = int64_t; using type = int64x2_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<float_t, 2>{ using scalar_type = float_t; using type = float32x2_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<float_t, 4>{ using scalar_type = float_t; using type = float32x4_t; using tag_type = vector_128_tag; };
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
-template <> struct neon_vector<float16_t, 4>{ using type = float16x4_t; using tag_type = vector_64_tag; };
-template <> struct neon_vector<float16_t, 8>{ using type = float16x8_t; using tag_type = vector_128_tag; };
+template <> struct neon_vector<float16_t, 4>{ using scalar_type = float16_t; using type = float16x4_t; using tag_type = vector_64_tag; };
+template <> struct neon_vector<float16_t, 8>{ using scalar_type = float16_t; using type = float16x8_t; using tag_type = vector_128_tag; };
 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 #endif /* DOXYGEN_SKIP_THIS */
 
diff --git a/arm_compute/runtime/NEON/NEFunctions.h b/arm_compute/runtime/NEON/NEFunctions.h
index 4e0cdd7..9460736 100644
--- a/arm_compute/runtime/NEON/NEFunctions.h
+++ b/arm_compute/runtime/NEON/NEFunctions.h
@@ -106,6 +106,7 @@
 #include "arm_compute/runtime/NEON/functions/NENonMaximaSuppression3x3.h"
 #include "arm_compute/runtime/NEON/functions/NENormalizationLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEOpticalFlow.h"
+#include "arm_compute/runtime/NEON/functions/NEPReluLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEPadLayer.h"
 #include "arm_compute/runtime/NEON/functions/NEPermute.h"
 #include "arm_compute/runtime/NEON/functions/NEPhase.h"
diff --git a/arm_compute/runtime/NEON/functions/NEPReluLayer.h b/arm_compute/runtime/NEON/functions/NEPReluLayer.h
new file mode 100644
index 0000000..52db427
--- /dev/null
+++ b/arm_compute/runtime/NEON/functions/NEPReluLayer.h
@@ -0,0 +1,59 @@
+/*
+ * Copyright (c) 2019 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef __ARM_COMPUTE_NEPRELULAYER_H__
+#define __ARM_COMPUTE_NEPRELULAYER_H__
+
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/INESimpleFunction.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/** Basic function to run @ref NEArithmeticOperationKernel for PRELU
+ *
+ * @note The function implements an activation layer with the PRELU activation function.
+ */
+class NEPReluLayer : public INESimpleFunction
+{
+public:
+    /** Set the input and output tensor.
+     *
+     * @param[in]  input  Source tensor. Data types supported: QASYMM8/F16/F32.
+     * @param[in]  alpha  Source alpha tensor. Data types supported: same of @p input.
+     * @param[out] output Destination tensor. Data type supported: same as @p input
+     */
+    void configure(const ITensor *input, const ITensor *alpha, ITensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEPReluLayer
+     *
+     * @param[in] input  Source tensor info. Data types supported: QASYMM8/F16/F32.
+     * @param[in] alpha  Source alpha tensor info. Data types supported: same of @p input.
+     * @param[in] output Destination tensor info. Data type supported: same as @p input
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *alpha, const ITensorInfo *output);
+};
+} // namespace arm_compute
+#endif /* __ARM_COMPUTE_NEPRELULAYER_H__ */