JensenShannon distance

float16_t riscv_jensenshannon_distance_f16(const float16_t *pA, const float16_t *pB, uint32_t blockSize)

float32_t riscv_jensenshannon_distance_f32(const float32_t *pA, const float32_t *pB, uint32_t blockSize)
 group JensenShannon
JensenShannon distance.
Functions
 __STATIC_INLINE float16_t rel_entr (float16_t x, float16_t y)

float16_t riscv_jensenshannon_distance_f16(const float16_t *pA, const float16_t *pB, uint32_t blockSize)
JensenShannon distance between two vectors.
This function is assuming that elements of second vector are > 0 and 0 only when the corresponding element of first vector is 0. Otherwise the result of the computation does not make sense and for speed reasons, the cases returning NaN or Infinity are not managed.
When the function is computing x log (x / y) with x == 0 and y == 0, it will compute the right result (0) but a division by zero will occur and should be ignored in client code.
 Parameters
pA – [in] First vector
pB – [in] Second vector
blockSize – [in] vector length
 Returns
distance
 __STATIC_INLINE float32_t rel_entr (float32_t x, float32_t y)

float32_t riscv_jensenshannon_distance_f32(const float32_t *pA, const float32_t *pB, uint32_t blockSize)
JensenShannon distance between two vectors.
This function is assuming that elements of second vector are > 0 and 0 only when the corresponding element of first vector is 0. Otherwise the result of the computation does not make sense and for speed reasons, the cases returning NaN or Infinity are not managed.
When the function is computing x log (x / y) with x == 0 and y == 0, it will compute the right result (0) but a division by zero will occur and should be ignored in client code.
 Parameters
pA – [in] First vector
pB – [in] Second vector
blockSize – [in] vector length
 Returns
distance