Current Issue : October - December Volume : 2019 Issue Number : 4 Articles : 5 Articles
As a classical DOA (direction of arrival) estimation algorithm, the multiple signal\nclassification (MUSIC) algorithm can estimate the direction of signal incidence. A major bottleneck in\nthe application of this algorithm is the large computation amount, so accelerating the algorithm to\nmeet the requirements of high real-time and high precision is the focus. In this paper, we design an\nefficient and reconfigurable accelerator to implement the MUSIC algorithm. Initially, we propose a\nhardware-friendly MUSIC algorithm without the eigenstructure decomposition of the covariance\nmatrix, which is time consuming and accounts for about 60% of the whole computation. Furthermore,\nto reduce the computation of the covariance matrix, this paper utilizes the conjugate symmetry\nproperty of it and the way of iterative storage, which can also lessen memory access time.................
The electronics industry in Taiwan has achieved a complete information and communication\ntechnology chain with a firm position in the global electronics industry. The integrated-circuit (IC)\npackaging industry chain adopts a professional division of labor model, and each process (including\nwafer dicing, die bonding, wire bonding, molding, and other subsequent processes) must have\nenhanced process capabilities to ensure the quality of the final product. Increasing quality can also\nlower the chances of waste and rework, lengthen product lifespan, and reduce maintenance, which\nmeans fewer resources invested, less pollution and damage to the environment, and smaller social\nlosses. This contributes to the creation of a green process. This paper developed a complete quality\nevaluation model for the IC packaging molding process from the perspective of a green economy.\nThe Six Sigma quality index (SSQI), which can fully reflect process yield and quality levels, is selected\nas a primary evaluation tool in this study. Since this index contains unknown parameters, a confidence\ninterval based fuzzy evaluation model is proposed to increase estimation accuracy and overcome the\nissue of uncertainties in measurement data. Finally, a numerical example is given to illustrate the\napplicability and eectiveness of the proposed method....
This paper reports design of a 2 * 4 hybrid multimode interferometer-Mach-zehnder\ninterferometer (MMI-MZI) configuration consiting of compact thermo-optical switches on the\nsilicon-on-insulator (SOI) platform. The device consists of two identical MMI slab waveguides\nas power splitters and couplers that are connected with two identical MMI-based phase shifters,\nand linear tapers at both ends of the MMIs to minimize the power coupling loss. A thin Al pad is\nused as a heating element and a trench is created around this pad to prevent heat from spreading, and\nto minimize loss. The calculated average thermo-optical switching power consumption, excess loss,\nand power imbalance are 1.4 mW, 0.9 dB, and 0.1 dB, respectively. The overall footprint of the device\nis 6 * 304 microm2. The new heating method has advantages of compact size, ease of fabrication on SOI\nplatform with the current CMOS technology, and offers low excess loss and power consumption\nas demanded by devices based on SOI technology. The device can act as two independent optical\nswitches in one device....
Discrete orthogonal transforms such as the discrete Fourier transform, discrete cosine\ntransform, discrete Hartley transform, etc., are important tools in numerical analysis, signal processing,\nand statistical methods. The successful application of transform techniques relies on the existence of\necient fast algorithms for their implementation. A special place in the list of transformations is\noccupied by the discrete fractional Fourier transform (DFrFT). In this paper, some parallel algorithms\nand processing unit structures for fast DFrFT implementation are proposed. The approach is based\non the resourceful factorization of DFrFT matrices. Some parallel algorithms and processing unit\nstructures for small size DFrFTs such as N = 2, 3, 4, 5, 6, and 7 are presented. In each case, we describe\nonly the most important part of the structures of the processing units, neglecting the description of\nthe auxiliary units and the control circuits....
This paper proposes a restricted coulomb energy neural network (RCE-NN) with an\nimproved learning algorithm and presents the hardware architecture design and VLSI implementation\nresults. The learning algorithm of the existing RCE-NN applies an inefficient radius adjustment,\nsuch as learning all neurons at the same radius or reducing the radius excessively in the learning\nprocess. Moreover, since the reliability of eliminating unnecessary neurons is estimated without\nconsidering the activation region of each neuron, it is inaccurate and leaves unnecessary neurons\nextant. To overcome this problem, the proposed learning algorithm divides each neuron region in\nthe learning process and measures the reliability with different factors for each region. In addition,\nit applies a process of gradual radius reduction by a pre-defined reduction rate. In performance\nevaluations using two datasets, RCE-NN with the proposed learning algorithm showed high\nrecognition accuracy with fewer neurons compared to existing RCE-NNs. The proposed RCE-NN\nprocessor was implemented with 197.8K logic gates in 0.535 mm2 using a 55 nm CMOS process and\noperated at the clock frequency of 150 MHz....
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