For mobile video codecs, the huge energy dissipation for external memory traffic is a critical challenge under the battery power constraint. Lossy embedded compression (EC), as a solution to this challenge, is considered in this paper. While previous studies in lossy EC mostly focused on algorithm optimization to reduce distortion, this work, to the best of our knowledge, is the first one that addresses the distortion control. Firstly, from both theoretical analysis and experiments for distortion optimization, a conclusion is drawn that, at the frame level, allocating memory traffic evenly is a reliable approximation to the optimal solution to minimize quality loss. Then, to reduce the complexity of decoding twice, the distortion between two sequences is estimated by a linear function of that calculated within one sequence. Finally, on the basis of even allocation, the distortion control is proposed to determine the amount of memory traffic according to a given distortion limitation. With the adaptive target setting and estimating function updating in each group of pictures (GOP), the scene change in video stream is supported without adding a detector or retraining process. From experimental results, the proposed distortion control is able to accurately fix the quality loss to the target. Compared to the baseline of negative feedback on non-referred B frames, it achieves about twice memory traffic reduction.

As the number of electronic control units (ECUs) or sensors connected to a controller area network (CAN) bus increases, so does the bus load. When a CAN bus is overloaded by a large number of ECUs, both the waiting time and the error probability of the data transmission are increased. Because the duration of the data transmission is proportional to the frame length, it is desirable to reduce the CAN frame length. In this paper, we present an improved CAN data-reduction (DR) algorithm to reduce the amount of data to be transferred in the CAN frame length. We also implement the data reduction algorithm using the CANoe software, and measure the CAN bus load using a CANcaseXL device. Experimental results with a Kia Sorento vehicle indicate that we can obtain additional average compression ratio of 11.15% with the proposed method compared with the ECANDC algorithm. By using the CANoe software, we show that the average message delay is within 0.10ms and the bus load can be reduced by 23.45% with 20 ECUs using the proposed method compared with the uncompressed message.

In this paper, the scan chain ordering method for BIST-aided scan test for reducing test data and test application time is proposed. In this work, we utilize the simple LFSR without a phase shifter as PRPG and configure scan chains using the compatible set of flip-flops with considering the correlations among flip-flops in an LFSR. The method can reduce the number of inverter codes required for inverting the bits in PRPG patterns that conflict with ATPG patterns. The experimental results for some benchmark circuits are shown to present the feasibility of our test method.

In this paper, we propose a scheme for test data reduction which uses broadcaster along with bit-flipping circuit. The proposed scheme can reduce test data without degrading the fault coverage of ATPG, and without requiring or modifying the arrangement of CUT. We theoretically analyze the test data size by the proposed scheme. The numerical examples obtained by the analysis and experimental results show that our scheme can effectively reduce test data if the care-bit rate is not so much low according to the number of scan chains. We also discuss the hybrid scheme of random-pattern-based flipping and single-input-based flipping.

MultiWave data compression algorithm is based on the multiresolution wavelet techniqu for decomposing Electrocardiogram (ECG) signals into their coarse and successively more detailed components. At each successive resolution, or scale, the data are convolved with appropriate filters and then the alternate samples are discarded. This procedure results in a data compression rate that increased on a dyadic scale with successive wavelet resolutions. ECG signals recorded from patients with normal sinus rhythm, supraventricular tachycardia, and ventriular tachycardia are analyzed. The data compression rates and the percentage distortion levels at each resolution are obtained. The performance of the MultiWave data compression algorithm is shown to be superior to another algorithm (the Turning Point algorithm) that also carries out data reduction on a dyadic scale.