In this article, the training-based channel estimation (TBCE) and semi-blind channel estimation (SBCE) schemes in Rayleigh flat fading multiple-input multiple-output (MIMO) channels are investigated. First, least squares (LS), linear minimum mean square error (LMMSE), maximum likelihood (ML), and maximum a posteriori (MAP) channel estimators are presented and simulated. Owing to faster processing and lower bit error rate (BER), the LS estimator is the proper choice for both TBCE and SBCE-ML. It is illustrated that when the number of transmitter and/or receiver antennas increases, the performance of both TBCE and SBCE-ML schemes significantly improves. In addition, Alamouti coding has more effect on the performance of SBCE-ML rather than TBCE. Comparing LS-based TBCE and LS-based SBCE-ML, the simulation results introduce the most appropriate channel estimation method that uses an iterative algorithm. This new proposed method is based on LS estimator and ML detector. Simulation results of this investigation show that LS-based SBCE-ML method compared with LS-based TBCE method in different signal-to-noise ratios (SNRs) offers lower BER, 25% higher processing time, and 100 times lower training bits.

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In this paper, a non-isolated inductor-capacitor-capacitor (LCC) topology based DC-DC converter for automotive application is practically implemented. The resonant tank with one inductor and two capacitors provides soft switching of the inverter switches and a voltage gain of 2. All possible LCC topologies are listed and categorized based on the order of their voltage gain expression. Based on the source/sink requirement for automotive application, some topologies are found to be realizable. For all these realizable topologies, voltage gain expressions are obtained and plotted against normalized frequency. From the voltage gain plots, one candidate topology is chosen and analyzed further. Expressions for current gain, stress across resonant tank elements, circulating reactive power and stored energy in the tank are obtained. The optimum value of Q which results in smallest possible resonant tank is determined and is found to be 0.545. The resonant tank is designed and implemented based on the optimum value of Q. Experimental results show that soft switching is achieved for a wide load range and is suitable for automotive application.

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Various switching-based median filters have been proposed in the literature for restoration of extremely corrupted images and video sequences by impulsive noise. Among these, switching median filters with boundary discriminative noise detection (BDND) are very effective and outperform all the previously proposed median-based filters. However, the calculation is very time-consuming. Hence, in this paper, a median filter with an efficient BDND (EBDND) is proposed for denoizing image and video sequences corrupted by impulsive noise. The proposed EBDND uses a faster sorting algorithm both in noise detection and adaptive filtering stages for the restoration of image and video sequences contaminated by impulse noise. For motion estimation of the video sequence, block-matching technique is used. The performance of the proposed EBDND is demonstrated through computer simulations in comparison with the BDND method.

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This paper presents an algorithm for content-based bit rate allocation for video coding in order to improve rate-distortion (R-D) performance. A fuzzy tool is developed to analyze different areas of a frame. This tool attributes a level of interest to each macroblock. It is effective for a very large range of natural pictures. Beginning with the segmentation of the original picture, a non-hierarchical fuzzy model allows combining the results of distinct criteria in order to increase the reliability of the system and provide convergence to a meaningful final result. R-D optimal rate allocation is done taking help of the fuzzy model and human visual system. The model developed is incorporated in TM5 rate control algorithm and the results are compared with the same.

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A special class of recursive multiplierless transforms for computing Discrete Cosine Transform (DCT) is introduced. DCT computation requires evaluation of cosine angles which are multiples of 2π/N. The proposed algorithm uses Ramanujan ordered number of degree-2 which is represented as 2^-l+2^-m. Thus the cosine functions can be computed by shifts and adds, employing Chebyshev type of recursion. With this algorithm, the floating-point multiplication is completely eliminated, and hence, the multiplierless algorithm can be implemented using shifts and additions only. The orthogonality of the recursive DCT kernel is well maintained through matrix factorization to reduce the computational complexity. The inherent parallel structure yields simpler programming and hardware implementation and provides 3/2Nlog₂N-N+1 additions and N/2log₂N shifts which is very much less complex when compared to other recent multiplierless algorithms.

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An Intel 8751 microcontroller-based system was developed to monitor and control the temperature of an oven. The IN4148 signal diode was used as the temperature sensor and the on-off control algorithm was utilized with the system switching off the heating process whenever it attains the preset value. The system provides a digital readout of the system temperature and a status/blinker indicator showing whether heating is in progress or terminated. The control programs were loaded onto the memory of the microcontroller and the enable the selection of the different temperature values. The system improves accuracy by eliminating human participation and saves operator time. The system is easy to operate, maintain, and upgrade.

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