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1.
This paper proposes a new approximation to be used for the correction function in the turbo decoding algorithm, called Linear-Constant-log Map. Max-log Map, Linear-log Map and Constant-log Map are the well known simplified versions of Jacobi-log Map (Maximum a Posteriori) algorithm already in use but they cannot meet a proper performance in term of output BER and clock consumption of the CPU decoding encoded bits. The proposed algorithm first breaks the correction function domain of the Jacobi logarithm to three subsections by determining the border points between these sections and then uses a linear function and two constant values as an approximation of this function. Using an AWGN channel model, simulation results show that the new algorithm is almost more than six times faster than Jacobi-log Map algorithm with a Bit Error Rate (BER) very close to it. 相似文献
2.
FFT速度的提高是数字信号处理领域中的核心问题,并行流水计算是实现大规模FFT高速计算的基本技术。在分析了基2时间抽取算法并行计算时输入数据的地址特性后,本文提出了2维SRAM的设计,它突破了并行计算N点FFT时普通SRAM地址非线性变化的瓶颈,达到 个蝶形单元并行流畅读写计算数据的目的,并使得数据地址数量变少,生成简单。本文对一个8×8字单元,每个字16比特的2维SRAM进行设计仿真,可以验证其功能正确。 相似文献
3.
采用Gr(o)bner基方法,可以把一个在有限群作用下不变的多项式写成不变环的生成元的多项式.核心问题是如何有效地计算这个正维不变理想的Gr(o)bner基.本文引入一个有效提升算法来计算这组Gr(o)bner基.当用straight line program模型对整个计算过程进行复杂度分析时,可以把计算开销控制在多项式时间内. 相似文献
4.
《Journal of The Franklin Institute》2023,360(8):5481-5503
Neural decoders were introduced as a generalization of the classic Belief Propagation (BP) decoding algorithms. In this work, we propose several neural decoders with different permutation invariant structures for BCH codes and punctured RM codes. Firstly, we propose the cyclically equivariant neural decoder which makes use of the cyclically invariant structure of these two codes. Next, we propose an affine equivariant neural decoder utilizing the affine invariant structure of those two codes. Both these two decoders outperform previous neural decoders when decoding cyclic codes. The affine decoder achieves a smaller decoding error probability than the cyclic decoder, but it usually requires a longer running time. Similar to using the property of the affine invariant property of extended BCH codes and RM codes, we propose the list decoding version of the cyclic decoder that can significantly reduce the frame error rate(FER) for these two codes. For certain high-rate codes, the gap between the list decoder and the Maximum Likelihood decoder is less than 0.1 dB when measured by FER. 相似文献
5.
采用Gröbner基方法,可以把一个在有限群作用下不变的多项式写成不变环的生成元的多项式.核心问题是如何有效地计算这个正维不变理想的Gröbner基.本文引入一个有效提升算法来计算这组Gröbner基.当用straight line program模型对整个计算过程进行复杂度分析时,可以把计算开销控制在多项式时间内. 相似文献
6.
《Information processing & management》2020,57(4):102248
In information retrieval, the task of query performance prediction (QPP) is concerned with determining in advance the performance of a given query within the context of a retrieval model. QPP has an important role in ensuring proper handling of queries with varying levels of difficulty. Based on the extant literature, query specificity is an important indicator of query performance and is typically estimated using corpus-specific frequency-based specificity metrics However, such metrics do not consider term semantics and inter-term associations. Our work presented in this paper distinguishes itself by proposing a host of corpus-independent specificity metrics that are based on pre-trained neural embeddings and leverage geometric relations between terms in the embedding space in order to capture the semantics of terms and their interdependencies. Specifically, we propose three classes of specificity metrics based on pre-trained neural embeddings: neighborhood-based, graph-based, and cluster-based metrics. Through two extensive and complementary sets of experiments, we show that the proposed specificity metrics (1) are suitable specificity indicators, based on the gold standards derived from knowledge hierarchies (Wikipedia category hierarchy and DMOZ taxonomy), and (2) have better or competitive performance compared to the state of the art QPP metrics, based on both TREC ad hoc collections namely Robust’04, Gov2 and ClueWeb’09 and ANTIQUE question answering collection. The proposed graph-based specificity metrics, especially those that capture a larger number of inter-term associations, proved to be the most effective in both query specificity estimation and QPP. We have also publicly released two test collections (i.e. specificity gold standards) that we built from the Wikipedia and DMOZ knowledge hierarchies. 相似文献
7.
MPEG-2是目前在视频通信中广泛应用的视频标准,由于其使用了VLC编码,增加了每个码流比特的重要性,而在某些复杂的传输环境中会引入很多噪声,这对视频解码的质量和完成都是有很大影响的。所以错误检测与掩盖技术在MPEG-2视频解码中非常重要。文章主要讨论MPEG-2解码器的噪声检测与错误掩盖的方法及其实现。 相似文献
8.
Ｈａｍｍｅｒｓｔｅｉｎ模型基于神经网络的预测控制方法 总被引：1，自引：0，他引：1
Ｈａｍｍｅｒｓｔｅｉｎ模型是化工过程中最常用的模型之一,它由非线性静态环节和线性动态环节串连 组成,适合描述ｐＨ过程和具有幂函数、死区、开关等非线性特性的过程．这类模型的控制问题可以分解 为：线性模型的控制问题和非线性模型的求根问题．针对Ｈａｍｍｅｒｓｔｅｉｎ模型提出了一种基于神经网络的 模型预测控制策略,采用一组神经网络拟合非线性部分的逆映射．这种方法不需要假设Ｈａｍｍｅｒｓｔｅｉｎ模 型的非线性部分由多项式构成,并且避免已有研究在无根和重根情况下存在的问题．最后通过仿真试验证明了以上结论． 相似文献
9.
《Information processing & management》2019,56(3):1026-1045
The study of query performance prediction (QPP) in information retrieval (IR) aims to predict retrieval effectiveness. The specificity of the underlying information need of a query often determines how effectively can a search engine retrieve relevant documents at top ranks. The presence of ambiguous terms makes a query less specific to the sought information need, which in turn may degrade IR effectiveness. In this paper, we propose a novel word embedding based pre-retrieval feature which measures the ambiguity of each query term by estimating how many ‘senses’ each word is associated with. Assuming each sense roughly corresponds to a Gaussian mixture component, our proposed generative model first estimates a Gaussian mixture model (GMM) from the word vectors that are most similar to the given query terms. We then use the posterior probabilities of generating the query terms themselves from this estimated GMM in order to quantify the ambiguity of the query. Previous studies have shown that post-retrieval QPP approaches often outperform pre-retrieval ones because they use additional information from the top ranked documents. To achieve the best of both worlds, we formalize a linear combination of our proposed GMM based pre-retrieval predictor with NQC, a state-of-the-art post-retrieval QPP. Our experiments on the TREC benchmark news and web collections demonstrate that our proposed hybrid QPP approach (in linear combination with NQC) significantly outperforms a range of other existing pre-retrieval approaches in combination with NQC used as baselines. 相似文献
10.
Julian Barreiro-Gomez Carlos Ocampo-Martinez Nicanor Quijano José M. Maestre 《Journal of The Franklin Institute》2017,354(14):5771-5796
This paper solves a data-driven control problem for a flow-based distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized non-cooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a non-complete information topology. Furthermore, an invariant-set property is presented and the closed-loop system stability is analyzed for the non-cooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical cooperative-games approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to large-scale problems. 相似文献
11.
L. Piroddi 《Journal of The Franklin Institute》2012,349(3):826-844
Nonlinear control with feedforward neural networks is usually designed by means of model based control strategies, which make explicit use of (direct or inverse) models of the controlled system. In this framework, a typical control problem consists in reducing the effects of the inevitable errors introduced by neural network approximation. In a non-adaptive setting, modeling errors can be compensated by hybrid control schemes, where the approximate neural controller is complemented with an integral type regulator connected in parallel. However, in this way, the model based control paradigm is partially lost and stability properties of the control system may be degraded. In this paper a stability analysis of such hybrid schemes is performed, which shows that control system stability can be achieved provided each of the two control blocks obeys a specific condition. Furthermore, a modified hybrid scheme is proposed to enhance the cooperation between the two control blocks: a nonlinear static filter is employed to modulate the integral action so that it becomes significant only when the neural controller has approached the equilibrium. Stability analysis is extended to this case. The hybrid scheme where the two control blocks are connected hierarchically in cascade is finally discussed. 相似文献
12.
Semantic image segmentation is a challenging problem from image processing where deep convolutional neural networks (CNN) have been applied with great success in the recent years. It deals with pixel-wise classification of an input image, dividing it into regions of multiple object classes. However, CNNs are opaque models. Given a trained CNN, it is hard to tell which information encoded in the input image is important for the network to perform segmentation. Such information could be useful to judge whether a trained network learned to segment in a plausible way or how its performance can be improved.For a trained CNN, we formulate an optimization problem to extract relevant image fractions for semantic segmentation. We try to identify a subset of pixels that contain the relevant information for the segmentation of one selected object class. In experiments on the Cityscapes dataset, we show that this is an easy way to gain valuable insight into a CNN trained for semantic segmentation. Looking at the relevant image fractions, we can identify possible limits of a trained network and draw conclusions about possible improvements. 相似文献
13.
排列组合是数学比较独特的一部分，是进一步学习概率的基础，同时这个知识模块也是考试必考的环节之一，知识虽然比较容易掌握，也比较有趣，但是题型非常多，本文主要根据自己的教学经验，总结排列组合解题的常用策略，希望能为教育工作者带来一些帮助。 相似文献
14.
Xinsong Yang Zunshui Cheng Xiaodi Li Tiedong Ma 《Journal of The Franklin Institute》2019,356(15):8138-8153
In this paper, new control scheme is considered for exponential synchronization of coupled neutral-type neural networks (NTNNs) with both bounded discrete-time delay and unbounded distributed delay (mixed delays). It is assumed that only the measured output can be utilized to design the controller. Quantized output controllers (QOCs) are considered to save the bits rate of communication channels and the bandwidth. The main difficulty in solving this problem is to cope with the neutral terms, the delays, and the uncertainties induced by the quantization simultaneously. By designing new Lyapunov–Krasovskii functionals and proposing novel analytical techniques, sufficient conditions are derived to ensure the exponential synchronization of the interested NTNNs. The control gains are given by solving a set of linear matrix inequalities (LMIs), which are not necessarily to be negative-definite matrices. Numerical examples are provided to verify the effectiveness and merits of the proposed approach. 相似文献
15.
《Information processing & management》2023,60(3):103265
Neural text transfer aims to change the style of a text sequence while keeping its original content. Due to the lack of parallel data, unsupervised learning-based approaches have gained considerable development. However, there are still several problems in these approaches: (1) The generated transferred sequences sometimes have inconsistencies between the transferred style and content, and (2) It is difficult to ensure sufficient preservation of the core semantics of original sequences in the transferred sequences. To address these defects, we propose Context-aware Style Learning and Content Recovery networks (CSLCR) for neural text transfer. Specifically, to improve the consistency between the transferred style and content, the designed context-aware style learning layer (CSL) retrieves target style samples with similar semantics to the original sequence, and promotes deep interactive fusion with the original sequence, so as to generate transferred sequence with context-aware style. To tackle the second problem, we explore content constraint recovery layer (CCR) from an indirect perspective, which decodes and recovers the core content semantics of the original sequence and the transferred sequence by both recovery decoding layers, respectively, and intensifies the preservation of the core semantics of both the sequences by a multi-level constraint mechanism. Experiments on two public datasets demonstrate the superiority of our proposed method. 相似文献
16.
Micro-blogging services such as Twitter allow anyone to publish anything, anytime. Needless to say, many of the available contents can be diminished as babble or spam. However, given the number and diversity of users, some valuable pieces of information should arise from the stream of tweets. Thus, such services can develop into valuable sources of up-to-date information (the so-called real-time web) provided a way to find the most relevant/trustworthy/authoritative users is available. Hence, this makes a highly pertinent question for which graph centrality methods can provide an answer. In this paper the author offers a comprehensive survey of feasible algorithms for ranking users in social networks, he examines their vulnerabilities to linking malpractice in such networks, and suggests an objective criterion against which to compare such algorithms. Additionally, he suggests a first step towards “desensitizing” prestige algorithms against cheating by spammers and other abusive users. 相似文献
17.
We investigate a new category of fuzzy-neural networks such as Hybrid Fuzzy Set-based Polynomial Neural Networks (HFSPNN). These networks consist of a genetically optimized multi-layer with two kinds of heterogeneous neurons such as fuzzy set-based polynomial neurons (FSPNs) and polynomial neurons (PNs). We have developed a comprehensive design methodology that helps determine the optimal structure of networks dynamically. The augmented genetically optimized HFSPNN (referred to as gHFSPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of gHFSPNN leads to the selection of preferred nodes (FSPNs or PNs) available within the HFSPNN. In the sequel, the structural optimization is realized via GAs, whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFSPNN is demonstrated through intensive experimentation where we use a number of modeling benchmarks—synthetic and experimental datasets are already being used in fuzzy or neurofuzzy modeling. 相似文献
18.
Martin Hilbert 《The Information Society》2014,30(2):127-143
This article asks whether the global process of digitization has led to noteworthy changes in the shares of the amount of text, images, audio, and video in worldwide technologically stored and communicated information content. We empirically quantify the amount of information that is globally broadcast, telecommunicated, and stored (1986–2007) and assess the evolution of the respective content shares. Somewhat unexpectedly, it turns out that the transfer from analog to digital has not led to toward increasing shares of media-rich audio and video content, despite vastly increased bandwidth. First, there is a certain inertia in the evolution of content, which seems to stick to stable proportions independent of its technological medium (be it analog vinyl and VHS tapes, or digital CDs and hard disks). Second, the relative share of text and still images actually captures a larger portion of the total amount than before the digital age. Text merely represented 0.3% of the (optimally compressed) bits that flowed through global information channels in 1986 but grew to almost 30% in 2007. On another level, we are seeing an increasing transition of text and images from one-way information diffusion networks (like newspapers) to digital storage and two-way telecommunications networks, where they are more socially embedded. Both tendencies are good news for big-data analysts who extract intelligence from easily analyzable text and image data. 相似文献
19.
This paper presents a new method for the performance evaluation of bit decoding algorithms. The method is based on estimating the probability density function (pdf) of the bit log likelihood ratio (LLR) by using an exponential model. It is widely known that the pdf of the bit LLR is close to the normal density. The proposed approach takes advantage of this property to present an efficient algorithm for the pdf estimation. The moment matching method is combined with the maximum entropy principle to estimate the underlying parameters. We present a simple method for computing the probabilities of the point estimates for the estimated parameters, as well as for the bit error rate. The corresponding results are used to compute the number of samples that are required for a given precision of the estimated values. It is demonstrated that this method requires significantly fewer samples as compared to the conventional Monte-Carlo simulation. 相似文献
20.
A microfluidic platform for size-dependent generation of droplet interface bilayer networks on rails
Droplet interface bilayer (DIB) networks are emerging as a cornerstone technology for the bottom up construction of cell-like and tissue-like structures and bio-devices. They are an exciting and versatile model-membrane platform, seeing increasing use in the disciplines of synthetic biology, chemical biology, and membrane biophysics. DIBs are formed when lipid-coated water-in-oil droplets are brought together—oil is excluded from the interface, resulting in a bilayer. Perhaps the greatest feature of the DIB platform is the ability to generate bilayer networks by connecting multiple droplets together, which can in turn be used in applications ranging from tissue mimics, multicellular models, and bio-devices. For such applications, the construction and release of DIB networks of defined size and composition on-demand is crucial. We have developed a droplet-based microfluidic method for the generation of different sized DIB networks (300–1500 pl droplets) on-chip. We do this by employing a droplet-on-rails strategy where droplets are guided down designated paths of a chip with the aid of microfabricated grooves or “rails,” and droplets of set sizes are selectively directed to specific rails using auxiliary flows. In this way we can uniquely produce parallel bilayer networks of defined sizes. By trapping several droplets in a rail, extended DIB networks containing up to 20 sequential bilayers could be constructed. The trapped DIB arrays can be composed of different lipid types and can be released on-demand and regenerated within seconds. We show that chemical signals can be propagated across the bio-network by transplanting enzymatic reaction cascades for inter-droplet communication. 相似文献