  Positional encodings are employed to capture the high frequency information
of the encoded signals in implicit neural representation (INR). In this paper,
we propose a novel positional encoding method which improves the reconstruction
quality of the INR. The proposed embedding method is more advantageous for the
compact data representation because it has a greater number of frequency basis
than the existing methods. Our experiments shows that the proposed method
achieves significant gain in the rate-distortion performance without
introducing any additional complexity in the compression task and higher
reconstruction quality in novel view synthesis.
