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A new algorithm for modular multiplication in the residue number system (RNS) is presented. Modular reduction is performed using a sum of residues. As all of the residues can be evaluated simultaneously, the algorithm permits a highly parallel implementation and is suitable for performing public-key cryptography operations with very low latency.
Discrete wavelet transform (DWT) has shown great performance in digital image compression and denoising applications. It is the transformation used for source encoding in JPEG2000 still image compression standard and FBI wavelet scalar quantization. DWT is capable of fast image compression at less area and low power consumption. This paper presents 4-tap(More)
Wavelets are powerful tools that can be used in signal processing and data compression. They are an excellent alternative to Fourier transforms for applications with transient input signals. There is a large volume of published studies describing the use of wavelets in various fields. However, properties of each family for designs with technology libraries(More)
Global techniques do not produce satisfying and definitive results for fingerprint image normalization due to the non-stationary nature of the image contents. Local normalization techniques are employed, which are a better alternative to deal with local image statistics. Conventional local normalization techniques involve pixelwise division by the local(More)
Modular multiplication can be performed in the residue number system (RNS) using a type of Montgomery reduction. This paper presents an alternative in which RNS modular multiplication are performed by using the core function. All of the intermediate calculations use short wordlength operations within the RNS. This work contributes to the long wordlength(More)