In this paper, we have proposed a new thermal-aware test data compression technique using dictionary based coding. Huge test data volume and chip temperature are two major challenges for test engineers. Temperature of...
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(纸本)9781479966585
In this paper, we have proposed a new thermal-aware test data compression technique using dictionary based coding. Huge test data volume and chip temperature are two major challenges for test engineers. Temperature of a chip can be reduced to a large extent by minimizing transition count in scan chains using efficient don't-care filling. On the other hand, high compression ratio can be achieved by filling the don't-cares intelligently to get more similar sub-vectors from test vectors. Although, both of the problems rely on don't-care bit filling, most of the existing works have considered them as separate problems. In our work, we have combined both temperature reduction and compression into a single problem and solved it. We present an intermediate approach that performs a trade-off between temperature and compression ratio. Experimental results on ISCAS'89 and ITC'99 benchmarks show the flexibility of the proposed method to achieve a balance between temperature and compression ratio.
In the recent years,microarray technology gained attention for concurrent monitoring of numerous microarray *** remains a major challenge to process,store and transmit such huge volumes of microarray ***,image compres...
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In the recent years,microarray technology gained attention for concurrent monitoring of numerous microarray *** remains a major challenge to process,store and transmit such huge volumes of microarray ***,image compression techniques are used in the reduction of number of bits so that it can be stored and the images can be shared *** techniques have been proposed in the past with applications in different *** current research paper presents a novel image compression technique i.e.,optimized Linde–Buzo–Gray(OLBG)with Lempel Ziv Markov Algorithm(LZMA)coding technique called OLBG-LZMA for compressing microarray images without any loss of *** model is generally used in designing a local optimal codebook for image *** construction is treated as an optimizationissue and can be resolved with the help of Grey Wolf Optimization(GWO)*** the codebook is constructed by LBGGWO algorithm,LZMA is employed for the compression of index table and raise its compression efficiency *** were performed on high resolution Tissue Microarray(TMA)image dataset of 50 prostate tissue samples collected from prostate cancer *** compression performance of the proposed coding esd compared with recently proposed *** simulation results infer that OLBG-LZMA coding achieved a significant compression performance compared to other techniques.
This paper proposes a new thermal-aware test data compression technique using dictionary-basedcoding. Large test data volume and rise in chip temperature during a test, are the two major challenges for the test engin...
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This paper proposes a new thermal-aware test data compression technique using dictionary-basedcoding. Large test data volume and rise in chip temperature during a test, are the two major challenges for the test engineers. Efficient filling of the don't care bits of the test patterns minimises the transition count in the scan chains, which in turn reduces the temperature of the chip to a large extent. On the other hand, high test data compression can be achieved by filling the don't-cares in a manner to get more similar sub-vectors within the test vectors. Although, both the problems rely on don't-care bit filling, most of the existing works have considered them separately. Moreover, it has been observed that, in general, thermal-aware don't-care filling leads to poor test compression, while a compression-aware don't-care filling produces high temperature. However, a high test compression with low-temperature is the most desirable expectation. In our work, we have combined the temperature reduction and the test data compression into a single problem and solved it. We have presented an integrated approach that can perform a trade-off between temperature and test compression. Experimental results on ISCAS'89, ITC'99 and IWLS'05 benchmarks show the flexibility of the proposed method to achieve a balance between temperature and test compression. The work has further been extended to reduce temperature without sacrificing compression.
In this paper, we propose a new encoder for scanned compound documents, based upon a recently introduced coding paradigm called multidimensional multiscale parser (MMP). MMP uses approximate pattern matching, with ada...
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In this paper, we propose a new encoder for scanned compound documents, based upon a recently introduced coding paradigm called multidimensional multiscale parser (MMP). MMP uses approximate pattern matching, with adaptive multiscale dictionaries that contain concatenations of scaled versions of previously encoded image blocks. These features give MMP the ability to adjust to the input image's characteristics, resulting in high coding efficiencies for a wide range of image types. This versatility makes MMP a good candidate for compound digital document encoding. The proposed algorithm first classifies the image blocks as smooth (texture) and nonsmooth (text and graphics). Smooth and nonsmooth blocks are then compressed using different MMP-based encoders, adapted for encoding either type of blocks. The adaptive use of these two types of encoders resulted in performance gains over the original MMP algorithm, further increasing the performance advantage over the current state-of-the-art image encoders for scanned compound images, without compromising the performance for other image types.
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