Algorithm for efficient interpolation of real-valued signals using discrete Hartley transform

Relation between Type-II Discrete Sine Transform and Type -I Discrete Hartley Transform

“…Replacing by in (13), we have (17) Multiplying (17) with -, we obtain (18) Using the identity (15) in RHS of (18), we have or (19) Adding (16) According to (2), the RHS of above expression represents the type-II discrete sine transform . Hence, we have (21) Since DST is given for , the output components of DST can be realized from DHT using (21).…”

“…Over the years, the DHT has been established as a potential tool for signal processing and communication applications, e.g., computation of circular convolution, and deconvolution [13], [14], interpolation of real-valued signals [15], image compression [16], [17], error control coding [18], adaptive filtering [19], multi-carrier modulation and many other applications [20]- [22]. Fast implementation of one-dimensional (1-D DHT) has attracted many attentions [23]- [25].…”

Fast Recursive Computation of Sliding DHT with Arbitrary Step

“…Discrete Hartley transform (DHT) [ 10 ] is used in various practical applications such as speech spectral analysis [ 11 ], feature extraction and sea surface modeling [ 12 ], data compression [ 13 ], and signal interpolation [ 14 ]. Four types of DHT are classified [ 15 , 16 ].…”

Fast computation of the discrete Hartley transform

“…Over the years, the discrete Hartley transform (DHT) [1] has been established as a potential tool for signal processing and communication applications, e.g. computation of convolution and deconvolution [2][3][4][5], interpolation of real-valued signal [6], image compression [7][8][9][10][11], error control coding [12], adaptive filtering [13][14][15][16], multi-carrier modulation and many other applications [17][18][19][20]. The DHT is known due to its real-valued symmetric transform kernel, which is identical to that of its inverse.…”