Symmetric Sum-Free Partitions and Lower Bounds for Schur Numbers
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c++计算梅尔频谱

c++计算梅尔频谱
C++计算梅尔频谱是一种信号处理技术,用于将一段音频信号转换为梅尔频率表示。
其基本思想是,人耳对不同频率的声音响应不同,因此将音频信号转换为梅尔频率表示可以更好地反映人耳对声音的
感知。
在C++中,计算梅尔频谱可以通过以下步骤实现:
1. 对音频信号进行预处理,如去除直流分量、加窗等操作。
2. 将音频信号分帧,每帧长度为N,帧之间相互重叠。
3. 对每帧信号进行FFT变换,得到其频谱。
4. 将得到的频谱转换为梅尔频率表示,通常采用以下公式:
mel = 2595 * log10(1 + f / 700)
其中,f为频率,mel为梅尔频率。
5. 将所有帧的梅尔频谱拼接成一个矩阵,作为最终的梅尔频谱表示。
C++中,可以使用FFT库和数学库来实现上述操作,如FFTW库和cmath库。
需要注意的是,在将频谱转换为梅尔频率时,需要定义一个频率到梅尔频率的映射关系,通常采用MelScale函数来实现。
- 1 -。
一种改进的tiny_YOLO_v3煤矸石快速识别模型

一种改进的tiny YOLO v3煤矸石快速识别模型郑道能(中煤西北能源化工有限公司,内蒙古 鄂尔多斯 017200)摘要:传统的煤矸石分选方法效率低下、安全隐患较大、应用范围受限,现有的基于机器视觉的煤矸石图像识别方法在模型识别速度与精度上难以平衡,未综合考虑输入图像尺寸不一、重要通道权重较低及卷积参数量大对模型精度的影响。
针对上述问题,在tiny YOLO v3模型的基础上,提出了一种改进的tiny YOLO v3煤矸石快速识别模型。
首先,在tiny YOLO v3模型引入多卷积核组合池化的特征金字塔池化(SPP )网络,确保输入特征图可被处理为固定尺寸再输出;其次,引入RGB 通道权重可调节的压缩激励(SE )模块,用于增强前几层特征图各通道之间的联系,强调感兴趣通道的特征值和不同目标特征之间的差异性,确保关键信息的捕捉和网络灵敏度;最后,引入包含0权值点的空洞卷积替代tiny YOLO v3模型中部分卷积层,在不增加模型参数的前提下,可捕获多尺度上下文信息进而扩大感受野,提高模型计算速度。
将该模型分别与tiny YOLO v3模型、Faster RCNN 模型、YOLO v5系列模型进行对比,结果表明:① 与tiny YOLO v3相比,改进的tiny YOLO v3煤矸石快速识别模型的识别准确性和快速性都有显著提升。
② 与Faster RCNN 相比,改进的tiny YOLO v3煤矸石快速识别模型训练时间减少了65.72%,识别精度增幅为11.83%,识别召回率增幅为0.5%,模型平均精度均值(mAP )增幅为3.02%。
③ 与YOLO 系列模型相比,改进的tiny YOLO v3煤矸石快速识别模型在保持识别精度优势的情况下识别速度有大幅增长。
消融实验结果表明:改进的tiny YOLO v3煤矸石快速识别模型的识别准确率为99.4%,较加入SPP 网络的tiny YOLO v3模型的识别准确率提高了4.9%;测试每张图片耗时12.5 ms ,较加入SPP 网络的tiny YOLO v3模型耗时减少了1 ms 。
【国家自然科学基金】_管理单元_基金支持热词逐年推荐_【万方软件创新助手】_20140731

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hive无分区表的开窗函数 -回复

hive无分区表的开窗函数-回复题目:Hive无分区表的开窗函数引言:在Hive中,分区表是一种重要的组织数据的方式,它可以提高查询性能,并提供更好的数据管理和分析功能。
然而,并非所有的表都适合进行分区,有时候我们可能需要使用无分区表进行数据操作和分析。
本文将深入探讨Hive无分区表的开窗函数,包括什么是开窗函数、为什么需要使用开窗函数以及如何在无分区表上使用开窗函数。
第一部分:什么是开窗函数开窗函数是一种在查询结果的每一行上计算多个值的函数,它可以通过在查询语句中定义窗口范围,来处理和操作数据。
开窗函数可以对数据进行排序、排名、汇总和聚合等操作,也可以计算滑动窗口内的数据聚合结果。
开窗函数通常用于解决实时分析、数据切片和滚动计算等问题。
第二部分:为什么需要使用开窗函数1. 简化计算逻辑:使用开窗函数可以将复杂的计算逻辑转化为单个查询,提高查询的可读性和可维护性。
2. 提高查询性能:开窗函数在查询过程中可以直接操作查询结果,无需多次扫描数据源,从而提高查询性能。
3. 实现更灵活的分析:开窗函数可以在不同的窗口范围内进行数据分析,更好地满足不同的分析需求。
4. 支持实时计算:开窗函数可以通过滑动窗口机制,对新的数据进行实时计算,适用于实时分析和实时决策场景。
第三部分:无分区表上使用开窗函数的注意事项在Hive中,无分区表是指没有按照任何特定列进行数据分区的数据表。
在无分区表上使用开窗函数时,需要注意以下几点:1. 数据排序:由于无分区表没有预定义的分区方式,需要手动指定数据的排序方式。
可以使用ORDER BY子句来对数据进行排序,以便开窗函数按照指定的顺序进行计算。
2. 窗口范围:定义窗口范围时,需要根据实际需求选择合适的窗口函数和窗口帧。
窗口函数包括ROW_NUMBER、RANK、DENSE_RANK等,窗口帧包括UNBOUNDED PRECEDING、CURRENT ROW等。
3. 数据量:无分区表上使用开窗函数时,需要考虑数据量的大小对查询性能的影响。
关联规则partition算法

关联规则partition算法一、概述关联规则是数据挖掘中的一种重要技术,它可以从大量的数据中挖掘出有用的信息,帮助企业做出决策。
而关联规则中的partition算法是一种常用的频繁项集挖掘算法,它能够高效地处理大规模数据集。
本文将详细介绍关联规则partition算法的原理、流程和实现方法,希望能够对读者有所帮助。
二、相关概念解释1. 关联规则关联规则是指在一个数据集中,两个或多个项之间存在着频繁出现的联系。
例如,在超市购物时,如果顾客购买了牛奶和面包,则很可能也会购买黄油。
因此,牛奶和面包与黄油之间就存在着关联规则。
2. 频繁项集频繁项集是指在一个数据集中经常同时出现的一组项。
例如,在超市购物时,如果某些商品组合经常被顾客购买,则这些商品就构成了一个频繁项集。
3. 支持度和置信度支持度是指一个频繁项集在整个数据集中出现的次数占比。
置信度是指当一个频繁项集出现时,另一个项也同时出现的概率。
三、partition算法原理1. 概述partition算法是一种基于数据分区的频繁项集挖掘算法。
它将数据集划分成若干个不相交的子集,然后在每个子集中进行频繁项集挖掘,最后将所有子集中的频繁项集合并得到全局频繁项集。
2. 算法流程(1)将数据集分为若干个不相交的子集;(2)在每个子集中进行频繁项集挖掘,得到局部频繁项集;(3)将所有子集中的局部频繁项集合并得到全局频繁项集。
3. 实现方法(1)数据分区:可以采用随机划分、轮换划分等方式将数据划分为若干个不相交的子集。
(2)局部频繁项集挖掘:可以采用Apriori算法等经典算法进行挖掘。
(3)全局频繁项集合并:可以采用多种方式进行合并,例如简单合并、位图压缩等。
四、实例演示以下是一个简单的关联规则partition算法实例:假设有如下购物清单:{牛奶,面包,黄油}{面包,黄油}{牛奶,面包,可乐}{牛奶,黄油}{面包,可乐}{可乐}将数据集划分为两个子集:S1:{牛奶,面包,黄油} {面包,黄油} {牛奶,面包,可乐}S2:{牛奶,黄油} {面包,可乐} {可乐}在每个子集中进行频繁项集挖掘:S1中的频繁项集为:{面包}、{黄油}、{牛奶, 面包}、{面包, 黄油}S2中的频繁项集为:{牛奶}、{黄油}、{可乐}将所有子集中的局部频繁项集合并得到全局频繁项集:全局频繁项集为:{面包}、{黄油}、{牛奶, 面包}、{面包, 黄油}、{牛奶}、{可乐}五、总结关联规则partition算法是一种高效的频繁项集挖掘算法。
A New Approach for Filtering Nonlinear Systems

computational overhead as the number of calculations demanded for the generation of the Jacobian and the predictions of state estimate and covariance are large. In this paper we describe a new approach to generalising the Kalman filter to systems with nonlinear state transition and observation models. In Section 2 we describe the basic filtering problem and the notation used in this paper. In Section 3 we describe the new filter. The fourth section presents a summary of the theoretical analysis of the performance of the new filter against that of the EKF. In Section 5 we demonstrate the new filter in a highly nonlinear application and we conclude with a discussion of the implications of this new filter1
Tቤተ መጻሕፍቲ ባይዱ
= = =
δij Q(i), δij R(i), 0, ∀i, j.
(3) (4) (5)
mfista算法

mfista算法MFISTA算法(Multifrontal Iterative Shrinkage-Thresholding Algorithm)是一种用于求解稀疏表示问题的迭代优化算法。
它在L1范数正则化的框架下,能够高效地求解具有稀疏性的信号重构问题。
稀疏表示问题是指在给定一组基函数的情况下,通过寻找最少的基函数线性组合来表示一个信号。
这个问题在信号处理、图像处理、机器学习等领域都有广泛的应用。
MFISTA算法的目标就是通过迭代的方式,找到一个最优的稀疏表示。
MFISTA算法的核心思想是通过将稀疏表示问题转化为一个优化问题,并采用了迭代收缩阈值的方式进行求解。
算法的具体步骤如下:1. 初始化:给定信号和基函数,初始化稀疏表示的值。
2. 迭代更新:通过迭代的方式不断更新稀疏表示的值,直至收敛。
在每一次迭代中,首先计算梯度,然后根据梯度信息进行更新。
3. 收缩阈值:在更新稀疏表示的过程中,需要进行阈值的选择。
MFISTA算法采用了一种自适应的阈值选择方法,称为FISTA步骤。
FISTA步骤通过计算两次迭代的差异来选择阈值,从而实现更好的收敛性能。
4. 结束条件:当稀疏表示的值不再发生显著变化时,算法收敛,可以得到最终的稀疏表示结果。
MFISTA算法相比于其他稀疏表示算法具有以下优点:1. 收敛速度快:MFISTA算法通过引入FISTA步骤,能够更快地收敛,提高算法的运行效率。
2. 稀疏性更好:MFISTA算法能够得到更加稀疏的稀疏表示结果,即使用更少的基函数来表示信号。
3. 适用性广:MFISTA算法在不同领域的稀疏表示问题中都有较好的应用效果,包括图像处理、压缩感知、信号恢复等。
4. 鲁棒性强:MFISTA算法对噪声和数据不完整性具有较好的鲁棒性,能够处理一些复杂的实际问题。
尽管MFISTA算法在稀疏表示问题中取得了较好的效果,但仍然存在一些局限性。
首先,算法的收敛性与初始化值有关,不同的初始化值可能导致不同的收敛结果。
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Symmetric Sum-Free Partitions and Lower Bounds for Schur NumbersHarold Fredricksen Naval Postgraduate School, Department of Mathematics, Monterey,CA93943,USA halF@Melvin M.SweetInstitute for Defense Analyses, Center for Communications Research, 4320Westerra Court,San Diego,CA92121,USAsweet@Submitted:May9,2000;Accepted:May18,2000AbstractWe give new lower bounds for the Schur numbers S(6)and S(7).This will imply new lower bounds for the Multicolor Ramsey Numbers R6(3)and R7(3).We also make several observations concerning symmetric sum-free partitions into5sets.IntroductionA set of integers is said to be sum-free if for all i and j≥i in the set the sum i+j is not in the set.The Schur number S(k)is defined to be the max-imum integer n for which the interval[1,n]can be partitioned into k sum-free sets.1I.Schur[7]proved that S(k)isfinite,and thatS(k)≥3S(k−1)+1.(1) In the framework of Ramsey theory,Schur’s proof yields the inequalityS(k)≤R k(3)−2,(2) where R k(n)denotes the k-color Ramsey number,defined to be the smallest integer such that any k-color edge coloring of the complete graph on R k(n) vertices has at least one complete subgraph all of whose edges have the same color.the electronic journal of combinatorics7(2000),#R322 It is easily verified that S(1)=1,S(2)=4,and S(3)=13;and L.D. Baumert[1]showed in1961with the aid of a computer that S(4)=44.The best known bounds for S(5)are160≤S(5)≤315(3) Thefirst inequality in(3)is due to G.Exoo[4],and the second follows from(2) and the bounds for R5(3)given in S.Radziszowski’s survey paper[6].For earlier work on lower bounds for S(k)see H.Fredricksen[5]and A.Beutelspacher and W.Brestovansky[2].The best previously known lower bound S(6)≥481for S(6)follows from (1).At the end of this note we list constructions that showS(6)≥536S(7)≥1680.Using(2)we obtain the following lower bounds for the Ramsey numbers R6(3) and R7(3):R6(3)≥538R7(3)≥1682.This improves the bounds given in Radziszowski’s survey paper.Note that the bound for R7(3)is better than the lower bound of1662that can be obtained by using F.Chung’s[3]inequalityR k+1(3)≥3R k(3)+R k−2(3)−3,for k≥3,with our new bound for R6(3).The constructions and results in this paper focus on symmetric partitions, where a sum-free partition P of the interval[1,n]is said to be symmetric if all symmetric pairs i and(n+1)−i are in the same set;except in the case when n+1is divisible by3,we must allow(n+1)/3and2(n+1)/3to be in different sets.There are no real theorems in this note,only observations and conjectures based on a computer study of symmetric sum-free partitions.We have restricted our focus to such partitions because the search space is smaller, and the concepts of equivalence and depth which are explained below provide additional useful structure for restricting the search.It is easy to see that if a symmetric sum-free partition P is multiplied mod(n+1)by an integer m that is relatively prime to n+1,then m P is also a symmetric sum-free partition.We will say two such partitions are equivalent.Given a partition P of[1,n],we define the depth,denoted d(P),to be the largest of the set minimums;and for a symmetric sum-free partition we define the e-depth,denoted D(P),to be the maximum of d(P )over all partitions P equivalent to P.We define D k(n)to be the maximum of D(P)over all symmetric sum-free partitions P of[1,n]into k sets.Note that we must haveD k(n)≤S(k−1)+1.the electronic journal of combinatorics7(2000),#R323 In a later section we will give exact values of D5(n)for many values of n. These values and other studies described later for partitions into5sets have led us to make the following conjectures:Conjecture1The largest integer for which there is a symmetric sum-free par-tition into5sets is160;and perhaps S(5)=160.Conjecture2All symmetric sum-free partitions of160into5sets have e-depth 44.Conjecture3There are no symmetric sum-free partitions of155or158into 5sets.Note155and158are the special cases in the definition of symmetric,and that it is not obvious that a symmetric partition of n into k sets implies that there is a symmetric partition of m into k sets for m<n.The Search AlgorithmThe search algorithm we used is the obvious branching scheme modified with various heuristics.We successively place an integer that is“most blocked”(in set membership)by earlier placements,and then backtrack when a branch dies or an answer is found.The heuristic used to decide which of the most blocked integers to select was to choose the smallest.Choosing the correct heuristic can make a huge difference in search ing this algorithm with the condition d(P)≥m,it is possible to completely exhaust the search tree in less than a minute for partitions of[1,n]into5sets with n near160and m near to44=S(4). For smaller depths the running time required to exhaust becomes excessive;but by limiting the total number of placements made beyond a certain level it is possible to probabilistically prune the search tree and have a good probability offinding an answer when one exists.Our search algorithm and heuristics were motivated by the following three observations that evolved during the development of the algorithm:1.It is easy to exhaustivelyfind all(not necessarily symmetric)sum-freepartitions into4sets.2.With high probability,it is easy to complete in a few steps a symmetricsum-free partition if only about20%of the elements are known.3.Many partitions are equivalent to partitions with large depth which canbe build byfirstfinding partitions in fewer sets.The partitions P of k=6and7sets given at the end of this paper were found using a probabilistic algorithm starting with a partition P of k−1sets with small d(P )and by restricting d(P)to be near S(k−1).the electronic journal of combinatorics7(2000),#R324 We believe that it should be possible tofind a larger lower bound for S(6)by looking for symmetric sum-free partitions that have large depth and have one other set with large e-depth.We currently have programs running to do this.Conjectures and Observations for5SetsThis section describes observations and conjections resulting from a computer study of symmetric sum-free partitions into5sets.By an exhaustive branching program,we were able to determine D5(n)for all n≤154.For102≤n≤154,D5(n)is always either44or45;for86≤n≤101, D5(n)is between41and45;and for45≤n≤85,D5(n)=[(n+1)/2].We were also able to determine that D5(160)=D5(157)=D5(156)=44,but that D5(159)=39.We were only able to show exhaustively that D5(155)<36and that D5(158)<36.A probabilistic search for symmetric sum-free partitions of 158into5parts,leads us to conjecture that there may be no such partitions; it is not obvious that a symmetric partition of n into k sets implies that there is a symmetric partition of m into k sets for m<n.A similar statement may apply to155,but we have not examined it as carefully.For160<n≤315 we exhaustively searched for symmetric partitions into5sets with depth≥44 and found that there are none.We did the same for other more relaxed depth restrictions,but for smaller n,with the same result;to summarizeD5(n)<36for161≤n≤190D5(n)<39for191≤n≤210D5(n)<44for211≤n≤315This,various probabilistic searches,and the upper bound in(3)leads us to conjecture that160is the largest integer for which there is a symmetric sum-free partition into5sets,and perhaps that S(5)=160.We found that there are symmetric sum-free partitions of157into5sets for each of the e-depths44,31,and26.For partitions of159into5sets,we found examples with D(P)=39and examples with D(P)=26.The only e-depth found for partitions of160into5sets was44.We conjecture that no other e-depths are possible for160into5sets.This would mean that all partitions of160’s would be equivalent to the5840we found exhaustively for 160with d=44;of these,768are equivalent to exactly one other partition with d(P)=44(interestingly,the equivalence multiplier is always30or59 (=−1/30mod161)),the rest were equivalent to no others with d(P)=44.So we conjecture that there are(4304+(768/2))∗φ(161)/2=309,408symmetric sum-free partitions of160into5sets.An interesting note for depth44symmetric sum-free partitions of160into 5sets is that the shortest distance between one and a multiple of another is small.Here the distance between partitions is defined as the smallest number of elements that are in different sets between the partitions,after a relabeling ofthe electronic journal of combinatorics7(2000),#R325 sets for one of the partitions.Considering only multiplication by1,30,and59 the maximum distance is19.This means that there is essentially only one cluster of depth44partitions,and if our conjecture is correct,then every symmetric partition is equivalent to something in this cluster.The situation in the last paragraph for160is similar to what happens for the largest partitions into4and3sets;further evidence that160may be maximal for5set partitions.For partitions of44into4sets all24=φ(45)symmetric sum-free partitions of the273sum-free partitions are equivalent(note that, since3divides45,multiplying by1and-1are not the same),and6of the24 have depth13.For sum-free partitions of13into3sets all three partitions are symmetric and equivalent.Another interesting aside,for depth44symmetric sum-free partitions of160 into5sets is that the sizes of the sets have the following properties:1.There are128different set size configurations.2.The largest set size is44,and the smallest is24.3.The largest difference between smallest and largest set in a partition is20,and the smallest is6.For the largest difference,the largest set is always44.For the smallest difference,the largest set is always34.4.The most likely set size configuration is{26,28,32,34,40},the electronic journal of combinatorics7(2000),#R326 ConstructionsThe constructions exhibited below are symmetric,and so we only list the small-est of a symmetric pair.Partition of536into6symmetric sumfree sets:Set1:1581114242730333640434649 526571778184909399103109112115125128131 134137144147150153160163166169172181185188191194 201204207213220223226229232235238242245248251254 264267358Set2:212192526344157586372798586 9596102118123124140141145146155156162173183193 200206211215216222233239244253260261266Set3:310162223293542485660626768 69747580878894100101106107113114119121126 133139151152158159164165171178184192197198203205 210217237241243249250255256Set4:4132028313850616473839198108 110117120132135142143154161168177179187195209212 214219221224231236246258265Set5:69172132394451545566708289 92104111127129130149167175189190202225227247252 262263Set6:715183745475359767897105116122 136138148157170174176180182186196199208218228230 234240257259268(D(P)=161)We also have constructions of6set partitions for the following n and respec-tive e-depths D:n=499,506,510,511,512,513,514,515,516,517,518,519,520,523,525,526,531 D=160,161,160,161,161,161,144,147,158,144,142,161,161,161,155,160,161.the electronic journal of combinatorics7(2000),#R327 Partition of1680into7symmetric sumfree sets:Set1:1151738525680828587899698109 129133135140142149151153158182184186190200206208 230237239241250253255261274283308318320334336352 371373389391415424428444446470477479486488493499 512521523525532541543546565567572574576583590596 627629643664666682684708717737750759761768770779 781800803810812814816821834Set2:22936425367738691100117124138147 155171188202209235240268280290291299306311317324 337350355361362383388393394421426432443459473476 481490506514528537544555561575588594599621626658 659665670681696697703714728740747752778785799832 Set3:38101221232830325061636870 7279818399101103105110112114121123130132134 141143150152154156161163165174176183185194196201 203205214221223232236238243245252254256258265267 272276278285287294296303305307314323325327329338 345347356358367374376380385387396398405407409420 427431438440447449456458460465467469471478480487 489491498507509511513518520522529531540542547551 558560562569573578580582591593600602609611613620 622624631633640644649662671673680691693695700706 711713715726731733735744746753757762773775777782 784793795797802806808813815817822824826828835837 Set4:41118203334356264657188115118 120167168170173217218220227242249270271273295297 300302309312326339348353370379406408411423425452 455461503505508533550564577605608617632646647661 663690699729741743780788789796811Set5:51439464749102104106136139189191192 199224233259262277284288315321340341342343344359 377403412429430437439441462474494496497515526527 538549556559579581597612614615623641650667668675 676678679694709712732734749764765767776794819820 829831Set6:69242526274143444555575859 74767792949597108111126127144145146159162 164177178179180193195197211212213215226229244246 247263264279282293330332333335346349364365366368the electronic journal of combinatorics7(2000),#R328 382384397399400402414416417418433434435448450451 453464466468482483484485500501502517534535536552 553568570571584585587603606618619634635637638652 653655656672685687688702704705718720721722723725 738755756758771772774787790791805809823825838840Set7:713161922313740485154606669 7578849093107113116119122125128131137148157 160166169172175181187198204207210216219222225228 231234248251257260266269275281286289292298301304 310313316319322328331351354357360363369372375378 381386390392395401404410413419422436442445454457 463472475492495504510516519524530539545548554557 563566586589592595598601604607610616625628630636 639642645648651654657660669674677683686689692698 701707710716719724727730736739742745748751754760 763766769783786792798801804807818827830833836839 (D(P)=537)We also have constructions of7set partitions forn=1615,1620,1630,1640,1650,1660,1665D=532,537,536,537,537,537,537. 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