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Carrefour Romania lanseaza colectia de toamna 2015 si website-ul tex.carrefour.ro

Carrefour Romania lanseaza colectia de toamna 2015 si website-ul tex.carrefour.ro

Carrefour România lansează noua colectie de toamna, ce propune tinute moderne, confortabile si de calitate, la preturi avantajoase, disponibila acum si pe noul site: tex.carrefour.ro.

Colectia de toamna 2015 vine cu oferte atragatoare de piese vestimentare, propunand o gamă variată de stiluri în tendintele acestei toamne: de la smart-casual, urban sau graphic pana la rock si retro. Cromatica acestui sezon se concentreaza pe tonuri neutre de alb, negru, gri sau albastru-bleumarin, care se imbina cu nuante aprinse de bordeaux, violet pruna si albastru electric, iar materialele de calitate cu texturi robuste precum denimul sau pielea ecologica complementează modelele fluide, pentru un stil mereu la modă.

Colectia continuă croielile drepte si liniile clasice, pentru un stil office, dar ofera si combinatii  versatile, pentru tinute nonconformiste celor cu spiritul tanar: cămăsi si rochii în printuri sau carouri, blugi clasici sau skinny, pulovere si jachete tricotate, alaturi de botine retro si accesorii sic, in culorile  sezonului.

„ Colectia de toamna 2015 continua directia cu care ne-am obisnuit deja clientii, oferind tinute cu atitudine si stil, moderne, confortabile si de calitate, la preturi accesibile tuturor. Si pentru a veni si mai aproape de ei, le punem la dispozitie o varianta usoara si interactiva de a fi in pas cu tendintele prin lansarea site-ului tex.carrefour.ro. Va invitam sa va alegeti tinutele preferate, pentru a da culoare si caracter acestei toamne.” a declarat Andreea Mihai, director de marketing al Carrefour România.

Mai mult, pentru a marca lansarea noii colectii, sambata, 19 septembrie, hipermarketurile Carrefour invita clientii sa participe la o Super Tombola unde pot castiga, din 30 in 30 de minute,  50% din valoarea unui articol vestimentar din cosul de cumparaturi.



In cadrul colectiei, gama TeX cuprinde:

TeX Basic - tinute de zi, comode, ce cuprind pantaloni, tricouri, cămăsi, jachete

TeX Casual - o categorie dedicată persoanelor care caută confortul, în tinute comode

TeX Sport – articole vestimentare sport, confectionate din materiale de calitate superioară: tesături anti-perspirante si rezistente la uzură

TeX Lenjerie - gama de lenjerie care se adresează atât femeilor si bărbatilor, cât si copiilor, ce include modele atractive, realizate din materiale de o calitate superioară

TeX Nightwear (pijamale) - îmbrăcăminte pentru noapte, din materiale textile plăcute si confortabile


Pentru un plus de inspiratie, vă invităm în magazinele noastre, sa incercati articolele vestimentare  sau sa descoperiti mai multe tinute din Colectia de Toamna 2015, direct pe noul site tex.carrefour.ro

 Cu peste 10.100 de magazine în 34 de tări, Grupul Carrefour este al doilea retailer mondial si numărul unu în Europa. De peste 50 de ani, Carrefour este un partener pentru viata de zi cu zi. În fiecare zi, acesta primeste în magazinele sale peste 10 milioane de clienti din lumea întreagă, oferindu-le o gamă largă de produse si servicii la preturi echitabile.

În România, Grupul Carrefour numără 180 de magazine dintre care 28 hipermarketuri 'Carrefour', 98 supermarketuri 'Market', 43 magazine de proximitate 'Express', 10 magazine de proximitate 'Contact' si un magazin de comert online: www.carrefour-online.ro.

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1. ä»‹ç» ä¼ ç»Ÿä¿¡å·æˆ–者图åƒé‡‡æ ·å¤šé‡‡å–香农采样定ç†ï¼šå³é‡‡æ ·é¢‘率为信å·é¢‘率最大值(那奎斯特采样频率)的二å€ã€‚本文æ出一ç§æ–°çš„ä¿¡å·å¤„ç†æ€è·¯â€”—压缩采样(CS)。在这ç§æ–°æ–¹æ³•ä¸‹ï¼Œé‡‡æ ·çŽ‡ä¼šå¤§å¤§é™ä½Žã€‚压缩采样ä¾èµ–两æ¡åŽŸåˆ™ï¼šç¨€ç–性和ä¸ç›¸å¹²æ€§ï¼Œå‰è€…从属于信å·ï¼ŒåŽè€…从属于感测模å¼ã€‚稀ç–性(sparsity):表达的概念是连续时间信å·çš„ä¿¡æ¯é‡‡é›†çŽ‡å¯èƒ½è¦æ¯”按带宽选择的采集率å°å¾—多,或者说离散时间信å·ä¾èµ–的自由度数è¦æ¯”他的长度å°çš„多,更明确的的说,压缩采样探索如下事实:许多自然信å·åœ¨ä¸‹è¿°æ„义下是稀ç–的或å¯åŽ‹ç¼©çš„:当用适当的基表示时,它们有更简æ´çš„表达。ä¸ç›¸å¹²æ€§ï¼ˆincoherence):延伸了时间与频率之间的对å¶æ€§ï¼Œå®ƒè¡¨è¾¾çš„概念是:正如时间域内的Dirac和尖峰信å·åœ¨é¢‘率域内是展开的那样,具有以$latex {\\Psi}&fg=000000$稀ç–表示的对象,在获å–它们的区域内一定是展开的。æžä¸ºé‡è¦çš„是人们å¯ä»¥è®¾è®¡å‡ºæœ‰æ•ˆçš„传感或采样方案,æ•æ‰åµŒå…¥åœ¨ç¨€ç–ä¿¡å·å†…有用的信æ¯å†…容,并将其压缩æˆå°‘é‡æ•°æ®ã€‚这些方法ä¸æ˜¯è‡ªé€‚应的,且åªéœ€è¦ä¸Žå°‘é‡çš„与æ供信å·ç®€æ´è¡¨è¿°ä¹‹åŸºä¸ç›¸å¹²ï¼ˆå¦åˆ™å°†å¤±åŽ»æµ‹é‡è¿‡ç¨‹å¯¹ä¿¡å·çš„ä¾èµ–性)的固定波形相关è”;此外,有利用数值优化由采集的少é‡æ•°æ®é‡æž„全长信å·çš„方法。æ¢è¨€ä¹‹ï¼ŒCS是一ç§éžå¸¸ç®€å•æœ‰æ•ˆçš„ä¿¡æ¯æ•èŽ·æ–¹æ³•ï¼Œå®ƒä»¥ä¸Žä¿¡å·æ— å…³çš„æ–¹å¼å’Œä½Žé‡‡æ ·çŽ‡é‡‡æ ·ï¼Œè€ŒåŽæ ¹æ®çœ‹ä¼¼ä¸å®Œæ•´çš„测é‡æ•°æ®é›†ç”¨è®¡ç®—能力é‡æž„ä¿¡å·ã€‚2. 感知问题 对于信å·$latex {f\\left(x\\right)}&fg=000000$,传感机制为:$latex \\displaystyle y_{k}=\\left\\langle f,\\varphi_{k}\\right\\rangle ,\\qquad k=1,\\ldots,m.\\ \\ \\ \\ \\ (1)&fg=000000$也就是说我们åªéœ€è¦å°†è¦èŽ·å¾—的对象与波形$latex {\\varphi_{k}}&fg=000000$相关è”,这是一个标准架构,例如,如果检测波形是Dirac delta(尖峰)函数,那么$latex {y}&fg=000000$就是$latex {f}&fg=000000$在时间或空间一个采样值的矢é‡ï¼›å¦‚果检测波形是åƒç´ çš„指示函数,那么$latex {y}&fg=000000$就是数字相机中传感器特别采集的图åƒæ•°æ®ï¼›æœ€åŽï¼Œå¦‚果检测波形是正弦函数,那么$latex {y}&fg=000000$就是Fourier系数,ç£å…±æŒ¯æˆåƒ (MRI)用的就是这ç§æ£€æµ‹æ¨¡æ€ã€‚尽管å¯ä»¥å»ºç«‹èµ·æ—¶ç©ºè¿žç»­çš„CSç†è®ºï¼Œä½†è¿™é‡Œåªå…³å¿ƒç¦»æ•£ä¿¡å·$latex {f\\in\\mathbb{R}^{n}}&fg=000000$,原因有二,一是简å•ï¼ŒäºŒæ˜¯çŽ°æœ‰ç†è®ºåœ¨æ­¤æƒ…况下æˆç†Ÿå¾—多。我们关心欠采样的情况,å¯å¾—到的测é‡æ•°$latex {m}&fg=000000$è¿œå°äºŽä¿¡å·$latex {f}&fg=000000$çš„ç»´æ•°$latex {n}&fg=000000$。由于å„ç§åŽŸå› ï¼Œè¿™ç§æƒ…å½¢æžä¸ºå¸¸è§ï¼Œè­¬å¦‚传感器数é‡æœ‰é™ï¼Œæˆ–者æŸäº›å€ŸåŠ©äºŽä¸­å­æ•£å°„获å–图åƒçš„花费æžä¸ºæ˜‚贵,或者是检测过程缓慢,象MRI那样åªèƒ½å¯¹å¯¹è±¡æ–½è¡Œå‡ æ¬¡æµ‹é‡ï¼Œç­‰ç­‰ã€‚这些情况产生一些é‡è¦é—®é¢˜ï¼Œæ ¹æ®$latex {m\\ll n}&fg=000000$次测é‡èƒ½å¤Ÿå‡†ç¡®çš„é‡æž„ä¿¡å·å—?能够设计出$latex {m\\ll n}&fg=000000$个检测波形æ•èŽ·åˆ°å‡ ä¹Žæ‰€æœ‰çš„关于$latex {f}&fg=000000$çš„ä¿¡æ¯å—?以åŠå¦‚何根æ®è¿™äº›ä¿¡æ¯é€¼è¿‘$latex {f}&fg=000000$?毫无疑问,这些都是困难的事情,因为å¯èƒ½éœ€è¦è§£æ¬ å®šçº¿æ€§æ–¹ç¨‹ç»„。令$latex {A}&fg=000000$是以$latex {\\varphi_{1}^{*},\\varphi_{2}^{*},\\varphi_{3}^{*}, ,\\varphi_{m}^{*}}&fg=000000$为行的$latex {m\\times n}&fg=000000$测é‡çŸ©é˜µï¼Œ$latex {\\varphi^{*}}&fg=000000$是$latex {\\varphi}&fg=000000$çš„å¤è½¬ç½®ã€‚当$latex {m0}&fg=000000$ä¸å¤§äºŽ$latex {O\\left(n^{-\\beta}\\right)}&fg=000000$,知中的指数是5而ä¸æ˜¯4(人们相信 对æ°ä¸º$latex {\\text{\\ensuremath{\\log}}n}&fg=000000$也是æˆç«‹çš„。这è¯æ˜Žå¯ä»¥ç¨³å®šè€Œå‡†ç¡®åœ°ç”±ä¸ç›¸å¹²åŸŸä¸­æˆå‰§æ€§çš„欠采样数æ®é‡æž„近稀ç–ä¿¡å·ã€‚最åŽï¼ŒçŸ©é˜µ$latex {A=\\Phi\\Psi}&fg=000000$也å¯ä»¥æˆç«‹çº¦æŸç­‰è·æ€§ï¼Œè¿™é‡Œ$latex {\\Psi}&fg=000000$是任æ„正交基,$latex {\\Phi}&fg=000000$是从适当分布中éšæœºæŠ½å–的测é‡çŸ©é˜µã€‚如果固定基$latex {\\Psi}&fg=000000$,按命题1~4æž„æˆæµ‹é‡çŸ©é˜µï¼Œå‡è‹¥ï¼š$latex \\displaystyle m\\geq C\\cdot\\log\\left(n/S\\right)\\ \\ \\ \\ \\ (15)&fg=000000$那么,$latex {A=\\Phi\\Psi}&fg=000000$将以æžå¤§çš„概率符åˆçº¦æŸç­‰è·æ€§ï¼ˆRIP);å¼ä¸­$latex {C}&fg=000000$为与具体情况有关的æŸä¸€å¸¸æ•°ã€‚è¿™ç§éšæœºæµ‹é‡çŸ©é˜µ$latex {\\Phi}&fg=000000$在æŸç§æ„义上是普适的,当设计测é‡ç³»ç»Ÿæ—¶ç”šè‡³ä¸éœ€çŸ¥é“稀ç–基。6. 什么是压缩采样? æ•°æ®èŽ·å–通常按下述方å¼å·¥ä½œï¼šå¤§é‡çš„æ•°æ®åªæ˜¯é‡‡é›†å‡ºæ¥ï¼Œå…¶ä¸­ä¸€å¤§éƒ¨åˆ†åœ¨åŽ‹ç¼©é˜¶æ®µè¢«æŠ›å¼ƒï¼Œä¸ºäº†å‚¨å­˜å’Œä¼ é€é€šå¸¸å¿…须这样åšã€‚用本文的è¯è¯´ï¼Œäººä»¬èŽ·å¾—高分辨率的åƒç´ æ•°ç»„$latex {f}&fg=000000$,计算完整的一套å˜æ¢ç³»æ•°ï¼Œå°†æœ€å¤§çš„系数编ç ï¼Œä¸¢æŽ‰å…¶å®ƒç³»æ•°ï¼Œå®žè´¨ä¸Šä»¥$latex {f_{S}}&fg=000000$结æŸï¼›è¿™ç§å¤§è§„模采集数æ®ç„¶åŽåŽ‹ç¼©çš„处ç†æ–¹æ³•æ˜¯æžä¸ºæµªè´¹çš„(å¯ä»¥æƒ³è±¡ä¸€ä¸‹æ•°å­—相机有百万åƒç´ çš„图åƒä¼ æ„Ÿå™¨ï¼Œè€Œæœ€ç»ˆç¼–ç çš„图åƒåªæœ‰å‡ ç™¾k字节)。CS的处ç†æžä¸ºä¸åŒï¼Œå…¶è¡¨çŽ°å¥½åƒæ˜¯èƒ½å¤Ÿç›´æŽ¥èŽ·å–处ç†å¯¹è±¡æ°ä¸ºæœ€é‡è¦çš„ä¿¡æ¯ã€‚通过å–如第5节的$latex {O(S\\log(n/S))}&fg=000000$个éšæœºæŠ•å½±ï¼Œäººä»¬å°±æœ‰è¶³å¤Ÿçš„ä¿¡æ¯é‡æž„ä¿¡å·ï¼Œå…¶ç²¾åº¦è‡³å°‘达到$latex {f_{S}}&fg=000000$具有的精度,得到处ç†å¯¹è±¡çš„最佳$latex {S}&fg=000000$项逼近和最优压缩表示。æ¢è¨€ä¹‹ï¼ŒCSæ•°æ®èŽ·å–å议实质上是把模拟信å·è½¬æ¢æˆåŽ‹ç¼©åŽçš„æ•°å­—å½¢å¼ï¼Œä½¿å¾—人们至少从原ç†ä¸Šå¯ä»¥ä»Žä»…有为数ä¸å¤šçš„传感器得到超分辨信å·ã€‚采集步骤åŽæ‰€æœ‰éœ€è¦åšçš„就是将测é‡æ•°æ®è§£åŽ‹ç¼©ã€‚料想ä¸åˆ°çš„是采集步是固定的,尤其是根本ä¸è¯•å›¾ç†è§£ä¿¡å·çš„结构,好åƒæ˜¯ã€Œä¸å¬å³é—»ã€ï¼ˆ hearing without listening)。CSåŒç¼–ç ç†è®ºï¼Œæ›´æ˜Žç¡®çš„说åŒReed-Solomonç¼–ç çš„ç†è®ºå’Œå®žè·µæœ‰æŸäº›è¡¨é¢ä¸Šçš„相似性。就本文讨论内容简å•åœ°è¯´ï¼Œå¦‚所周知,å¯ä»¥é‡‡ç”¨ç¼–ç ç†è®ºçš„概念如下建立CS:人们å¯ä»¥æ ¹æ®ä¿¡å·çš„å‰$latex {2S}&fg=000000$个 Fourier系数$latex \\displaystyle {y_{k}}=\\sum\\limits _{t=0}^{n-1}{{x_{t}}{e^{-i2\\pi kt/n}}},\\quad k=0,1,2,\\ldots,2S-1\\ \\ \\ \\ \\ (16)&fg=000000$或者从相继$latex {2S}&fg=000000$个信å·é¢‘率集唯一的é‡æž„任何$latex {S}&fg=000000$-稀ç–ä¿¡å·ï¼ˆå¤åŽŸä¿¡å·çš„计算æˆæœ¬å®žè´¨ä¸Šæ˜¯è§£$latex {S\\times S}&fg=000000$ Toeplitz矩阵,或计算$latex {n}&fg=000000$点FFT),这æ„味ç€å¯ä»¥ç”¨è¿™ä¸€æ–¹æ³•æµ‹é‡å¯åŽ‹ç¼©ä¿¡å·å—?由于两个原因答案是å¦å®šçš„。其一,Reed-Solomon解ç æ˜¯ä»£æ•°æ–¹æ³•ï¼Œä¸èƒ½ç”¨äºŽéžç¨€ç–ä¿¡å·ï¼ˆè§£ç æ˜¯é€šè¿‡æ±‚多项å¼çš„根寻找信å·æ”¯æ’‘集);其二,根æ®ä¿¡å·çš„å‰$latex {2S}&fg=000000$个Fourier系数寻找信å·æ”¯æ’‘集的问题,甚至当信å·å…·å¤‡å‡†ç¡®ç¨€ç–性时,是éžå¸¸ä¸é€‚定的(这个问题与由少é‡å€¼é«˜åº¦é›†ä¸­çš„数预测高阶多项å¼ç›¸åŒï¼‰ï¼›å“ªæ€•ç³»æ•°å—到微å°çš„扰动也会导致完全ä¸åŒçš„答案,这使得用有é™ç²¾åº¦çš„æ•°æ®å¯é åœ°è®¡ç®—支撑集在实际上是ä¸å¯èƒ½çš„。å之,纯粹代数方法忽略了信æ¯ç®—å­çš„调节作用,使å–得良æ€çŸ©é˜µï¼Œè¿™æ˜¯ç²¾ç¡®ä¼°è®¡çš„关键,正如约æŸç­‰è·æ€§æ‰€èµ·ä½œç”¨æ˜¯CS所关心的中心问题。7. 应用 å¯åŽ‹ç¼©ä¿¡å·å¯ä»¥ç”¨ä¸Žä¿¡æ¯æ°´å¹³$latex {S\\ll n}&fg=000000$æˆæ­£æ¯”的若干ä¸ç›¸å¹²æµ‹é‡æ•èŽ·ï¼Œè¿™ä¸€äº‹å®žæœ‰ç€æ·±è¿œçš„æ„义并涉åŠåˆ°è®¸å¤šå¯èƒ½çš„应用。数æ®åŽ‹ç¼©ï¼šå¯¹æ•°æ®åŽ‹ç¼©è€Œè¨€ï¼Œåœ¨æŸäº›æƒ…况下解ç å™¨ä¸Šç¨€ç–基å¯èƒ½æ˜¯æœªçŸ¥çš„,或者施行起æ¥ä¸å®žç”¨ã€‚然而正如第五节所讨论的éšæœºè®¾è®¡çš„$latex {\\Phi}&fg=000000$å¯è§†ä¸ºæ™®é€‚解ç ç­–略,因为它ä¸éœ€è¦å›´ç»•$latex {\\Psi}&fg=000000$的结构设计(åªæœ‰è§£ç æˆ–å¤åŽŸ$latex {f}&fg=000000$æ—¶æ‰éœ€å…·å¤‡$latex {\\Psi}&fg=000000$的知识和实现$latex {\\Psi}&fg=000000$的能力)。这ç§æ™®é€‚性特别有助于诸如传感器网络之类的多信å·è£…置的编ç ã€‚关于这个问题请读者å‚考Nowak等人 åŠGoyal在其它地方的论文。信é“ç¼–ç ï¼šæ­£å¦‚文献{[}15{]}所解释的那样,å¯ä»¥å›´ç»•CS的原ç†ï¼ˆç¨€ç–性,éšæœºæ€§ï¼Œå’Œå‡¸ä¼˜åŒ–)并将其用于设计快速纠错ç ï¼Œé¿å…错误信å·çš„传输。å问题:对于其它一些情况,获å–$latex {f}&fg=000000$的唯一方法å¯èƒ½æ˜¯ç”¨æŸç§æ¨¡æ€çš„测é‡ç³»ç»Ÿ$latex {\\Phi}&fg=000000$,å‡å®šä¸Ž$latex {\\Phi}&fg=000000$ä¸ç›¸å¹²$latex {f}&fg=000000$的稀ç–基$latex {\\Psi}&fg=000000$存在。就有å¯èƒ½è¿›è¡Œæœ‰æ•ˆçš„测é‡ï¼Œä¸€ä¸ªåº”用涉åŠåˆ°MR血管造影术和其它类型的MR设备;在这些例å­ä¸­$latex {\\Phi}&fg=000000$记录$latex {f}&fg=000000$çš„Fourierå˜æ¢çš„å­é›†ï¼Œæ‰€å¸Œæœ›çš„图åƒ$latex {f}&fg=000000$在时间域和å°æ³¢åŸŸéƒ½æ˜¯ç¨€ç–的。其它领域的这个问题Lustig等人有更深入的讨论。数æ®é‡‡é›†ï¼šæœ‰æ—¶å…¨éƒ¨æµ‹é‡æ¨¡æ‹Ÿä¿¡å·çš„n个离散时间样本å¯èƒ½éš¾ä»¥å¾—到(而且接下æ¥ä¹Ÿéš¾ä»¥åŽ‹ç¼©ï¼‰ã€‚在这ç§æƒ…况下,å¯èƒ½æœ‰åŠ©äºŽè®¾è®¡å‡ºç‰©ç†é‡‡æ ·è®¾å¤‡ï¼Œç›´æŽ¥è®°å½•ä¼ å…¥æ¨¡æ‹Ÿä¿¡å·ç¦»æ•£çš„ã€ä½Žé‡‡æ ·çŽ‡çš„ä¸ç›¸å¹²æµ‹é‡ã€‚最åŽä¸€ä¸ªåº”用暗示我们,数学和计算方法å¯èƒ½ä¼šå¯¹ä¼ ç»Ÿçš„硬件设计有é™åˆ¶çš„领域产生巨大的冲击。如传统的图åƒè®¾å¤‡é‡‡ç”¨CCDå’ŒCMOS技术基本上é™äºŽå¯è§†å…‰è°±ï¼Œè€ŒCS相机用数字微型镜头阵列采集ä¸ç›¸å¹²æ•°æ®ï¼Œä¹Ÿè®¸èƒ½å¤Ÿæ˜Žæ˜¾æ‰©å……其能力。关于这个问题其它地方的讨论,以Baraniuk讨论这ç§ç›¸æœºæ›´åŠ æ·±å…¥ã€‚有一部分研究者已专心于大带宽高级模拟-ä¿¡æ¯ï¼ˆA/I)转æ¢è®¾å¤‡çš„研究,目标是帮助å‡è½»ä¼ ç»Ÿæ¨¡æ‹Ÿ-数字(A/D)转æ¢æŠ€æœ¯çš„压力,当å‰è¯¥æŠ€æœ¯é™äºŽ1GHz的采样速度。作为å¯é€‰æ‹©çš„方案,我们建议两ç§ç‰¹æ®Šçš„ã€å¯ä»¥ä»Žé«˜å¸¦å®½æ¨¡æ‹Ÿä¿¡å·ä¸­èŽ·å¾—离散的ã€ä½Žé‡‡æ ·çŽ‡ï¼Œä¸ç›¸å¹²æµ‹é‡åºåˆ—çš„A/I架构。对高阶逼近,æ¯ä¸€ä¸ªæµ‹é‡$latex {y_{k}}&fg=000000$,都å¯ä»¥è§£é‡Šä¸ºå…¥å°„模拟信å·$latex {f}&fg=000000$与模拟测é‡æ³¢å½¢$latex {\\varphi_{k}}&fg=000000$的内积$latex {\\left\\langle f,\\varphi_{k}\\right\\rangle }&fg=000000$,正如在离散CS框架那样,我们的åˆæ­¥ç»“果表明éµå¾ªç¨€ç–或å¯åŽ‹ç¼©æ¨¡åž‹ï¼ˆåœ¨æŸä¸€æ¨¡æ‹Ÿå­—å…¸$latex {\\Psi}&fg=000000$中)的信å·å¯ä»¥ç”¨è¿™äº›è®¾å¤‡ä»¥æ­£æ¯”于信æ¯æ°´å¹³è€Œä¸æ˜¯é‚£å¥Žæ–¯ç‰¹é¢‘率有效的æ•èŽ·ã€‚当然,利用离散CS方法å¤åŽŸæ¨¡æ‹Ÿç¨€ç–ä¿¡å·æœ‰å¾…å…‹æœçš„挑战性问题。全é¢è§£å†³è¿™äº›é—®é¢˜è¶…出了本短文的范围;人们å¯ä»¥ç®€å•çš„接å—å…¶æ€æƒ³ï¼Œç¦»æ•£/采样稀ç–å­—å…¸å…许适当的å¤åŽŸã€‚我们有两个架构如下:}~éžå‡åŒ€é‡‡æ ·å™¨ï¼ˆNUS):此架构åªæ˜¯æŠŠéšæœºé‡‡æ ·æ—¶é—´ç‚¹ä¸Šçš„ä¿¡å·æ•°å­—化,å³$latex {{y_{k}}=f\\left({t_{k}}\\right)=\\left\\langle {f,{\\delta_{{t_{k}}}}}\\right\\rangle }&fg=000000$,事实上这些éšæœºæˆ–伪éšæœºæ—¶é—´ç‚¹æ˜¯é€šè¿‡æŠ–动规则格å­ä¸Šçš„å义(低采样率)采样点得到的。由于尖峰与正弦信å·ä¸ç›¸å¹²ï¼Œå› æ­¤è¿™ç§æž¶æž„å¯ç”¨äºŽå¯¹å…·æœ‰è¿œä½ŽäºŽé‚£å¥Žæ–¯ç‰¹é¢‘率的稀ç–频谱信å·é‡‡æ ·ã€‚当然与å‡å°‘采样率有关的好处是æžå¤§çš„,因为这æ供了附加电路稳定时间,并具有å‡å°å™ªå£°æ°´å¹³çš„作用。éšæœºé¢„积分(RPI):此架构å¯ç”¨äºŽç§ç±»æ›´å¹¿æ³›çš„稀ç–域,在时间-频率平é¢æœ‰ç¨€ç–特å¾çš„最显著的那些信å·ã€‚鉴于没有å¯èƒ½ä»¥æžé«˜çš„采样率将模拟信å·æ•°å­—化,而æžæœ‰å¯èƒ½ä»¥å¾ˆé«˜çš„速率改å˜å®ƒçš„æžæ€§ã€‚RPI架构的æ€æƒ³ï¼ˆè§å›¾5)就是以正1和负1的伪éšæœºåºåˆ—乘以信å·ï¼Œå°†ä¹˜ç§¯åœ¨æ—¶é—´çª—å£ç§¯åˆ†ï¼Œå°†æ—¶æ®µæœ«çš„积分值数字化,这是一个并行架构,有若干个这样的乘法器-积分器对用完全ä¸åŒçš„甚至几乎独立的éšæœºç¬¦å·åºåˆ—并列è¿è¡Œã€‚事实上RPI架构将信å·åŒ$latex {\\pm1}&fg=000000$符å·åºåˆ—库相关è”,是普适的CS测é‡æ–¹æ³•ä¹‹ä¸€ã€‚对上述æ¯ä¸ªæž¶æž„,我们都曾用数值的方法确认,有些还用物ç†çš„方法è¯å®žï¼Œç³»ç»Ÿå¯¹äºŽç”µè·¯éžç†æƒ³ï¼Œå¦‚热噪声ã€æ—¶é’Ÿè¯¯å·®ã€å¹²æ‰°åŠæ”¾å¤§å™¨éžçº¿æ€§ç­‰æƒ…况是é²æ£’性的。将A/I架构应用于实际采集方案还需è¦å‘展CS算法和ç†è®ºï¼ŒåŒ…括研究模拟信å·ç¨€ç–表示的字典。我们以最åŽä¸€ä¸ªç¦»æ•£çš„例å­ç»“æŸã€‚对这个实验,我们å–$latex {f}&fg=000000$是长度$latex {n=512}&fg=000000$çš„1-Dä¿¡å·ï¼ŒåŒ…å«ä¸¤ä¸ªè°ƒåˆ¶è„‰å†²ï¼ˆå›¾6左侧),从这个信å·ä¸­æˆ‘们用以独立åŒåˆ†å¸ƒæŸåŠªåˆ©$latex {\\pm1}&fg=000000$元素填充生æˆçš„$latex {m\\times n}&fg=000000$测é‡çŸ©é˜µ$latex {\\Phi}&fg=000000$, 采集$latex {m=30}&fg=000000$次测é‡ï¼Œè¿™æ˜¯ä¸åˆç†çš„å°æ•°æ®é‡ï¼Œæ¬ é‡‡æ ·å› å­è¶…过17。为了é‡æž„ä¿¡å·ï¼Œæˆ‘们考虑时-频Gaborå­—å…¸$latex {\\Psi}&fg=000000$,它由Gaussian窗é™æ—¶å¹¶å…·æœ‰ä¸åŒä½ç½®å’Œå°ºåº¦çš„å„ç§æ­£å¼¦æ³¢æž„æˆã€‚总的说字典是过完备($latex {43\\times}&fg=000000$overcomplete)的,ä¸å«åŒ…括$latex {f}&fg=000000$的两个脉冲。图6中间图形表示å–$latex {{\\left\\Vert x\\right\\Vert _{{\\ell_{1}}}}}&fg=000000$æžå°åŒ–使$latex {y=\\Phi\\Psi x}&fg=000000$,é‡æž„效果显示出明显的人为效应,我们看到$latex {{\\left\\Vert {f-{f^{*}}}\\right\\Vert _{{\\ell_{2}}}}/{\\left\\Vert f\\right\\Vert _{{\\ell_{2}}}}\\approx0.67}&fg=000000$,而事实上我们通过将两者都å˜ä¸º$latex {\\ell_{1}}&fg=000000$å¤åŽŸæ–¹æ³•ï¼Œå°±å¯ä»¥æ¶ˆé™¤äººä¸ºæ•ˆåº”。首先,我们改用æžå°åŒ–$latex {{\\left\\Vert {\\Psi*\\tilde{f}}\\right\\Vert _{{\\ell_{1}}}}\\; s.t.\\; y=\\Phi\\tilde{f}}&fg=000000$;(当$latex {\\Psi}&fg=000000$是正交基时这一改å˜ä¸èµ·ä½œç”¨ï¼‰ï¼›å…¶æ¬¡ï¼Œå½“得到估计值$latex {f^{*}}&fg=000000$时我们将$latex {\\ell_{1}}&fg=000000$-范数é‡æ–°åŠ æƒï¼Œé‡å¤é‡æž„过程,对那些估计较大的系数采用较低的惩罚值;图6å³å›¾æ˜¾ç¤ºäº†é‡å¤åŠ æƒ4次迭代的结果,我们看到$latex {{\\left\\Vert {f-{f^{*}}}\\right\\Vert _{{\\ell_{2}}}}/{\\left\\Vert f\\right\\Vert _{{\\ell_{2}}}}\\approx0.022}&fg=000000$。有关这个新方å‘的更多信æ¯ï¼Œå»ºè®®è¯»è€…å‚阅文献{[}30{]}。在此,给出的è¦ç‚¹æ˜¯ï¼Œå³ä¾¿è¿™ä¸ªæ•°æ®é‡å°åˆ°è’谬的地步,人们ä»å¯ä»¥æ•èŽ·åˆ°ä¿¡å·é‡ŒåŒ…å«çš„ç»å¤§éƒ¨åˆ†ä¿¡æ¯ã€‚这就是CS在当å‰ä»¥åŠæœªæ¥åº”用æžæœ‰å‰é€”的原因。a0References[1] E.J. Cand`es, J. Romberg, and T. Tao. Robust uncertainty principles: Exact signal reconstructionfrom highly incomplete frequency information. Information Theory, IEEE Transactionson, 52(2):489–509, 2006.[2] E.J. Candes and T. Tao. Near-optimal signal recovery from random projections: Universalencoding strategies? Information Theory, IEEE Transactions on, 52(12):5406–5425, 2006.[3] D.L. Donoho. Compressed sensing. Information Theory, IEEE Transactions on,52(4):1289–1306, 2006.[4] A. Bilgin, M.W. Marcellin, and M.I. Altbach. Compression of electrocardiogram signals usingJPEG2000. Consumer Electronics, IEEE Transactions on, 49(4):833–840, 2003.[5] D.L. Donoho and X. Huo. Uncertainty principles and ideal atomic decomposition. InformationTheory, IEEE Transactions on, 47(7):2845–2862, 2001.[6] R. Coifman, F. Geshwind, and Y. Meyer. Noiselets. Applied and Computational HarmonicAnalysis, 10(1):27–44, 2001.[7] J.F. Claerbout and F. Muir. Robust modeling with erratic data. 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