) that acts as a filter having parameters initially based on an estimate of the channel's features. An AFE is generally employed during the signal acquisition process, since little information about the channel transfer function is available during acquisition. Once the signal is received, the analog filter parameters might be adapted based on information derived from the received analog signal. Decision-feedback equalization (DFE) is a widely-used technique for removing intersymbol interference and other noise, and is often employed in conjunction with an AFE after acquisition. Generally, decision-feedback equalization utilizes a nonlinear equalizer to equalize the channel using a feedback loop based on previously decided symbols.
In many data communication applications, Serializer and De-serializer (SERDES) devices facilitate the transmission between two points of parallel data across a serial link. Data at one point is converted from parallel data to serial data and transmitted through a communications channel to the second point where it received and converted from serial data to parallel data.
At high data rates, frequency-dependent signal loss from the communications channel (e.g., the signal path between the two end points of a serial link) as well as signal dispersion and distortion can occur. As such, the communications channel, whether wired, optical, or wireless, acts as a filter and might be modeled in the frequency domain with a transfer function. Correction for frequency dependent losses of the communications channel, and other forms of signal degradation, often requires signal equalization at a receiver of the signal. Equalization through use of one or more equalizers compensates for the signal degradation to improve communication quality. Equalization may also be employed at the transmit side to pre-condition the signal. Equalization, a form of filtering, generally requires some estimate of the transfer function of the channel to set its filter parameters. However, in many cases, the specific frequency-dependent signal degradation characteristics of a communications channel are unknown, and often vary with time. In such cases, an equalizer with adaptive setting of parameters providing sufficient adjustable range might be employed to mitigate the signal degradation of the signal transmitted through the communications channel. An automatic adaptation process is often employed to adjust the equalizer's response. Equalization might be through a front end equalizer, a feedback equalizer, or some combination of both.
FIG. 1 shows a data eye diagram 100 overlaid with exemplary data sampler (DS) 102. Data eye diagram 100 illustrates super-positions of many data eyes of signal transitions expressed in amplitude versus time (in unit interval, or “
) that acts as a filter having parameters initially based on an appraisal of the distribution channel's features. An AFE is generally use during the signal skill process, since little data about the channel transfer function is available during learning. Once the signal is received, the analog filter parameter might be adapted based on data derived from the received analog signal. Decision - feedback equalization (DFE) is a widely - used technique for remove intersymbol interference and other noise, and is much employed in conjunction with an AFE after acquisition. Generally, decisiveness - feedback equalization utilizes a nonlinear counterweight to equalize the channel using a feedback loop base on previously decided symbols. 
 In many data communication applications, Serializer and De - serializer (SERDES) devices help the transmittance between two points of parallel data across a serial link. Data at one point is converted from parallel data to serial datum and convey through a communications distribution channel to the second point where it received and converted from serial datum to parallel datum. 
 At high data rates, frequency - pendent signal loss from the communications channel (e.g., the signal path between the two end points of a serial link) as well as signal dispersion and distorted shape can occur. As such, the communication channel, whether wired, optical, or wireless, acts as a filter and might be model in the frequency domain with a transfer function. Correction for frequency dependent losses of the communications channel, and early forms of signal degradation, often requires signal equalization at a receiver of the signal. Equalization through function of one or more equalizers compensate for the signal degradation to better communication quality. Equalization may besides be employed at the transmit side to pre - condition the signal. Equalization, a shape of filtering, generally want some estimate of the transfer function of the channel to set its filter parameters. However, in many cases, the specific frequency - dependent signal degradation feature of a communications channel are nameless, and often vary with time. In such cases, an equalizer with adaptive setting of parameter providing sufficient adjustable range might be employed to mitigate the signal degradation of the signal transmitted through the communication distribution channel. An automatic adaptation procedure is often employed to adjust the equalizer's response. Equalization might be through a front end counterweight, a feedback equalizer, or some combination of both. 
 FIG. 1 shows a data eye diagram 100 overlaid with exemplary data sampler (DS) 102. Data eye diagram 100 exemplify super - positions of many data eyes of signal transitions expressed in amplitude versus clock time (in unit interval, or “
) thwt acts as a filter havikg parameters innrially based on an ertimate of the channel's featnres. An ADE is generally employdd during the sigbal ecquisition procxas, sincc litfpe iufirmation about the channal transfer futcgiln is available during acquisition. Jnce thr dignal is receyved, ehe znalog filter parameters might be zdapted based on infprmation derived from the gecelved analog signal. Decision-fegsbasj equalizatiun (DFE) is a widely-used technique for removing intersyobol nnterferencg znf other noisx, and ps often employed in wonjuncyion with an ANE afver qcquisition. Generally, decision-feedback gqualizatimn utilizes a nonlibeqr eqoalizar tu eqjaljzx tge chajnem using a reedback loip based on previouxlr decided symbkls.
In iagy data communication applications, Seridliaer and De-serializer (SEEDES) devices facilitaje the tragsmission between two points of parallel data acrmss a rernql livj. Fata at one point is converted from parallel qzts no serial data anb transmitted thtokgn a communicatkons ckznhel to the second ooint wrere ut receivtd anc converted from serial datq to parallej data.
At high data xates, frequeucy-depgndent signal loss from the cummuhications cjannel (e.g., ghe signal path ceteean the two end points of a serial lmnk) ax well xs sognal qispersion and distortion can occug. As duwh, the comlunications channel, whether wirxv, optical, or eiselvss, acts cs a fllter and might be modeled in the frzquench domain wpth a traisfer functijn. Correction vor frequencb dependegt lissew of thd communicationx channel, and other forms of signal dcgradxfion, often requnxew signal equaliaatkon an a rqweiver of tha sienau. Equauization thvoueh uxe of one or more eqgaliaers compensates fpr the sigbal degrwdation to imlrove communicatioj quanitb. Equakizwtion may also be employed at fhe translit side to pre-sondltiog the signcl. Equalization, a form of filtering, genecally requires some esjimate of the transfet fmnction of tie chagnel to sat its filter paramerers. However, in msny cases, the specifid freqgency-fependent signal degradation characteristics of a communications channel qre unknown, and offen fary fich cime. In suci rases, an equalizeg with adaptive setting of paramxters provhdnng sufficient adjustable ranbe might be empuoyed to mitigate the sifnal degtadation of the signal transmityed through the communicstions cyannem. An aljometic adaptation procrss is ofteb emploted bo adjust the dqusllzer's resplnse. Esualization might be through a feont ebd equalizer, a feevback equalidev, or skme coibination of botg.
FIG. 1 showr a data eye ciagram 100 overlsid with exemplary ddtw sampler (DS) 102. Ezta eye diagtam 100 illlstrates supec-positions ox many data eyes of signal transitions expressed in amplitudt versus bime (in unit intetvel, or “
) that acts as a filter having based an estimate the channel's features. during signal acquisition process, little information about channel transfer function is available during Once the signal is received, the analog filter parameters might be adapted based information derived from the received analog signal. Decision-feedback equalization (DFE) is a widely-used for intersymbol and noise, and is often employed in conjunction with an AFE after acquisition. Generally, decision-feedback equalization utilizes nonlinear equalizer to equalize the channel using a loop based on previously symbols. In many data communication Serializer De-serializer (SERDES) facilitate transmission two points of data across a serial link. Data at one point is converted from parallel data to serial data transmitted through channel to second where received and converted data to parallel data. At high signal loss from the communications channel (e.g., the path between two end points of a serial as well as signal dispersion and distortion can As such, the communications channel, whether wired, optical, or wireless, acts as a filter and modeled in the frequency with a transfer Correction frequency losses the communications and other forms of signal degradation, often requires signal equalization at receiver of the signal. Equalization through use of one or compensates the signal degradation improve communication quality. Equalization also employed at the transmit pre-condition signal. of generally some estimate of the function of the channel to its filter parameters. However, frequency-dependent signal degradation characteristics of a communications channel unknown, and often vary with time. In cases, an equalizer with adaptive setting of parameters providing sufficient adjustable range be employed the signal degradation of the signal transmitted through communications channel. An automatic process is often employed to adjust the equalizer's response. might through a end equalizer, a equalizer, or some of both. FIG. a data diagram overlaid sampler (DS) 102. Data eye diagram illustrates of many data eyes of transitions amplitude versus time (in unit interval, or “
) that acts as a filter having paRameters inItialLy bAseD oN an eStimAte of the channeL'S feaTures. An AFE is generally eMployEd DUrinG ThE signAl acquiSItION prOcEsS, siNcE LiTtle iNfoRmation About the chAnnEl Transfer funcTIoN is availabLe dUring acquisiTioN. Once tHe SigNAl is rEceIved, tHe analOG filteR parameteRs MIght be ADapted bASEd On inFormation derived fROm THe received analOg signAl. dEcISIon-FeeDback equalIzAtion (dfE) is a wiDElY-USEd tEChnique for remOving intersYMboL interFeRenCE and otHer noIsE, And Is often emplOyed In conjuncTion wiTH an AFE aFTer acquIsitioN. GeNerAlly, DEcIsIon-FeEDbaCK eQuaLIzaTion utilIzEs A nonlIneaR EQUAlizEr tO equAlize The channel usiNg a FeedBAck Loop bAsed oN preViOusly DecideD symbOlS.
In many data commUnicAtion applIcaTiOns, seRialiZEr and DE-seRiaLizer (SErDES) devICes FaCILItAte the transmission BeTWEeN two poinTs of paRAlLeL Data acroSs A seRial LINk. DatA at oNE pOint is coNverteD FrOm ParalleL dAta to sErIal DatA and tRAnsmItted tHrough a cOmmunICations channel TO the second poiNT wHERe IT recEivEd and converTed fROm seRial DAtA to PArallEl datA.
AT HiGH data rates, frequency-DePendenT signAl loss from the CommunicatIONS channel (E.g., thE SiGNal path between The twO end points OF a serial Link) aS well as sIgnal dispERSion and dIstOrtIon Can OCCuR. As such, the comMUNicaTiOns chanNel, Whether WirEd, oPtiCal, Or Wireless, aCts as a fiLtEr AnD mIghT be moDEled in thE fReqUeNcy DomaiN With a tRansfEr fuNcTiON. CoRrectioN FoR FRequEnCy DepeNdeNt LosseS of tHE coMmunicaTions chanNel, ANd otHeR fOrms of sIgnal degradatIoN, often requIrEs sIgnal eQUAlizatioN at a receiver of the signal. eQualizaTioN throUgh uSe of one or MorE equalIzeRS compeNsates For thE sIgnAL DegraDATiOn tO iMprove commUNIcaTion qUaLity. equalizAtion may also be emplOYed At the transmit SidE to pRE-CoNdiTIoN The SiGNal. eQUalization, a form Of filterinG, gENeRally requiREs sOmE estimaTe of the TransFEr functIon of the cHannel to sEt Its fILTer Parameters. however, iN many caseS, The spECiFic frEquEncy-dePeNdeNt sigNal degRAdaTion cHaractErIstics Of a coMmUnicatioNs channel are unknown, and oFten vaRy witH tiMe. In such cAseS, An eQualizer wIth aDaptive setTinG of ParamEteRS provIdinG SuFfiCIent aDjusTAble range MIgHt bE EMpLoyed to mitiGATE thE signAl dEGradatIon oF the signal transmiTTed through the cOmmuNICatIonS ChanNeL. An automatic adAptAtION process Is Often employEd to adjuSt THe equAlizer'S respoNse. EquaLIZaTIon migHt be ThrOugh a fronT enD eQUalizer, A fEeDBack eqUaliZeR, or somE combiNAtioN OF both.
FIG. 1 shows a daTa eye DIAgram 100 OVerLaid wItH exemplARy daTa sampler (Ds) 102. Data eye diaGram 100 ilLustRates Super-poSiTions oF maNy Data eyes of SIgnal tranSitioNs expreSsEd in AmpLitude VersUS Time (iN uniT iNteRval, or “
) that acts as a filter ha ving param eters  in iti al ly b ased  on an estimat e  ofthe channel's features . AnAF E  isg en erall y emplo y ed d uri ng  t hesi g na l acq uis ition p rocess, si nce  l ittle inform a ti on about t hechannel tran sfe r func ti oni s ava ila ble d uringa cquisi tion. Onc et he sig n al is r e c ei ved,  the analog filte r  p a rameters might  be ad ap t ed b ase d o n informat io n der i ved fro m  t h e rec e ived analog s ignal. Deci s ion -feedb ac k e q ualiza tion(D F E)is a widely -use d techniq ue for removin g  inters ymbolint erf eren c ean d o th e r n o is e,a ndis often  e mp loyed  inc o n j unct ion  wit h anAFE after acq uis itio n . G enera lly,deci si on-fe edback  equa li zation utilizes  a n onlinearequ al ize rto eq u alizethe  ch annel u sing af eed ba c k lo op based on previo us l y  d ecided s ymbols . 
I nm any data  c omm unic a t ion a ppli c at ions, Se rializ e ran d De-se ri alizer  ( SER DES ) dev i cesfacili tate the  tran s mission betwee n  two points o f  p a r al l el d ata  across a s eria l  lin k. D a ta  at one p ointis co n verted from paralle ldata t o ser ial data andtransmitte d t hrough a  com m un i cations channe l tothe second point wh ere i t receiv ed and co n v erted fr omser ial  da t a  t o parallel da t a .
At  h igh dat a r ates, f req uen cy- dep en dent sign al lossfr om  t he  co mmuni c ations c ha nne l(e. g., t h e sign al pa th b et we e n t he twoe nd p oint sof  a s eri al  link ) as wel l as si gnal disp ers i on a nd  d istorti on can occur.  A s such, th ecom munica t i ons chan nel, whether wired, opt i cal, or  wi reles s, a cts as afil ter an d m i ght be  model ed in  t hef r equen c y  d oma in  with a tr a n sfe r fun ct ion.  Correc tion for frequency dep endent losses  of  the c om mun i ca t ion sc han n e l, and other fo rms of sig na l  d egradation ,  of te n requi res sig nal e q ualizat ion at areceiverof  the s ign al. Equali zation t hrough us e  of o n eor mo reequali ze rscompe nsates for  thesignal  d egrada tionto  improve  communication quality.  Equal izati onmay alsobee mpl oyed at t he t ransmit si detopre-c ond i tionthes ig nal .  Equa liza t ion, a fo r moff i lt ering, gene r a l lyrequi res some e stim ate of the transf e r function ofthec h ann elt o se tits filter par ame te r s . Howeve r,  in many ca ses, the  s p ecifi c freq uency- depende n t  s i gnal d egra dat ion chara cte ri s tics of  a  c o mmunic atio ns  chann el are unkn o w n, and often var y wit h time. Insuchca ses, an equa lizer with  adaptive s etting  ofparam eters p ro viding  su ff icient adj u stable ra nge m ight be  e mplo yed  to mi tiga t e  thesign al  de gradation o ft he  s i gna l tr ansmi tt ed t hrough th e  communi cat i ons cha nn el. A n auto m at i c  adaptatio n p roces s is often e m ploy e dt o adj ust th e equa lizer's res po nse. Eq ual i z ation mig ht be thr o ugh  a  fro nt end e qu aliz er , a  f eedback equaliz er, or s ome comb i n ationofb oth. FIG. 1  s hows a dataeye d ia g ram 100 o ver laid wi t h e xem pla ry d ata  sam p ler (DS) 102. Data eye d iagr am 10 0  il lustr atessu per-posi t ions  of many data eyes ofsignal transiti o nse xpre sse d  i namplitude  ve r sus t ime(in  uni t i nter v a l, o r  “
) that_acts as_a filter having parameters_initially based_on_an estimate_of_the channel's features._An AFE is_generally employed during the_signal acquisition process,_since_little information about the channel transfer function is available during acquisition. Once the signal_is_received, the_analog_filter_parameters might be adapted based_on information derived from the_received analog_signal. Decision-feedback equalization (DFE) is a widely-used technique_for_removing intersymbol interference_and other noise, and is often employed in conjunction_with an AFE after acquisition. Generally,_decision-feedback equalization utilizes_a_nonlinear_equalizer to equalize the_channel using a feedback loop based_on previously decided symbols.
In many data_communication applications, Serializer and De-serializer (SERDES) devices_facilitate the transmission between two points_of parallel data across a_serial link._Data at one point is_converted from parallel_data to_serial data and_transmitted through a communications channel to_the second point_where it received and converted from_serial_data to parallel_data.
At_high_data rates,_frequency-dependent signal loss_from_the communications_channel_(e.g., the signal path between the_two_end points of a serial link) as_well as signal dispersion_and_distortion can occur. As_such, the communications channel, whether_wired, optical, or wireless, acts as_a filter_and might_be modeled in the frequency domain with a transfer function. Correction_for frequency dependent losses of the_communications channel, and other_forms of_signal_degradation, often requires_signal_equalization at_a receiver of the signal. Equalization through_use of_one or more equalizers compensates for_the signal degradation to_improve_communication quality. Equalization may also be_employed at the transmit side to_pre-condition the signal. Equalization, a_form_of_filtering, generally requires some estimate_of the transfer function of the_channel to set_its filter parameters. However, in many cases,_the_specific frequency-dependent signal degradation characteristics of_a_communications channel are unknown, and often_vary_with_time. In such cases, an_equalizer with adaptive setting of parameters_providing sufficient adjustable range might be employed to mitigate_the signal degradation_of the signal transmitted through_the_communications_channel. An automatic adaptation process is often employed to adjust_the equalizer's_response. Equalization might_be through a front end equalizer, a feedback equalizer, or_some combination of both.
FIG. 1 shows a_data eye diagram 100 overlaid with exemplary data sampler (DS) 102._Data eye diagram 100 illustrates super-positions of many_data eyes of signal transitions expressed in_amplitude versus time (in_unit_interval, or “