جستجوی مقالات مرتبط با کلیدواژه « decoder » در نشریات گروه « برق »

The shrinking of transistor dimensions and migration to nanometer region have increased the data storage errors in new generations of flash memories. Therefore, the reliability of data storage is an important challenge in the structure of these memories. In order to confront with this challenge, BCH error correction codes are utilized in the controller of these memories. There are two important points in the optimization process of a BCH decoder: speeding up the computation and reducing the hardware complexity. To speed up the decoding process, a parallel architecture is utilized for various building blocks. A Pipeline scheme is also adopted in BCH decoder to increase the throughput. To implement this parallel BCH decoder in an area-efficient manner, an iterative matching scheme is proposed to reduce the Chien search hardware complexity by reducing the number of XOR gates through removing the duplicate gates and sharing the remaining ones. The proposed decoder along with BCH encoder have been implemented in VHDL hardware definition language and synthesized in Xilinx ISE. The proposed decoder has been implemented in VHDL hardware definition language and synthesized in Xilinx ISE. The simulation results show that the proposed algorithm could reduce the decoding time and hardware complexity .

Videos are made up of a temporal sequence of frames and are projected at a proper rate to create the illusion of motion. This means that there exists a high correlation between adjacent temporal frames so that when projected at a proper rate, smooth motion is seen. Correlation between adjacent temporal frames is called interframe correlation. In order to decode compressed video bit stream uniformly by various platforms and devices, the bit stream format must be predefined. Thus, there must be a standard for a video compressor, which will enable all standard-compliant compressed video data to be decoded anywhere. The goal is to propose a new video compression algorithm based on wavelet transform and neural networks. Using wavelet transform leads to factorization in temporal as well as spatial domain. The goal in this paper is to achieve a compression algorithm which would be faster and has more compression ratio. Neural networks are used for prediction which is one of the most important functions in any video compression scheme. Furthermore, the proposed algorithm is compared with MPEG standard. Simulation results show the befits of using wavelet transform which reveal that the proposed algorithm is faster and has better performance in some aspects compared to MPEG standard. The video which obtained from proposed algorithm has acceptable in human visual and since it needs less than space for storing, it is suitable for portable devices.