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}
T {ANALOG AUDIO AMPLIFIER
N-Channel only power stage} 430 -270 0 0 0.5 0.5 {layer=8}
N 180 -500 180 -470 {lab=E9}
N 260 -470 340 -470 {lab=E9}
N 340 -500 340 -470 {lab=E9}
N 1110 -700 1110 -670 {lab=SA}
N 840 -1020 840 -980 {lab=E4}
N 1110 -590 1110 -570 {lab=OUTI}
N 1110 -510 1110 -470 {lab=#net1}
N 180 -1020 180 -980 {lab=E1}
N 390 -790 520 -790 {lab=C2}
N 230 -950 230 -900 {lab=#net2}
N 180 -900 230 -900 {lab=#net2}
N 390 -790 390 -740 {lab=C2}
N 340 -740 390 -740 {lab=C2}
N 180 -920 180 -900 {lab=#net2}
N 220 -950 230 -950 {lab=#net2}
N 340 -760 340 -740 {lab=C2}
N 380 -790 390 -790 {lab=C2}
N 180 -1120 180 -1080 {lab=VBOOST}
N 840 -1120 840 -1080 {lab=VBOOST}
N 180 -1120 690 -1120 {lab=VBOOST}
N 690 -1120 840 -1120 {lab=VBOOST}
N 1110 -1180 1400 -1180 {lab=VPP}
N 840 -1120 1240 -1120 {lab=VBOOST}
N 860 -440 1070 -440 {lab=GB}
N 560 -460 560 -440 {lab=C8}
N 1240 -1120 1400 -1120 {lab=VBOOST}
N 1240 -900 1240 -870 {lab=#net3}
N 560 -580 560 -520 {lab=E8}
N 560 -760 560 -640 {lab=C6}
N 840 -780 840 -760 {lab=GA}
N 690 -810 690 -790 {lab=B1}
N 690 -810 800 -810 {lab=B1}
N 690 -1120 690 -880 {lab=VBOOST}
N 690 -820 690 -810 {lab=B1}
N 260 -470 260 -460 {lab=E9}
N 150 -70 260 -70 {lab=VSS}
N 50 -210 220 -210 {lab=B3}
N 260 -180 260 -130 {lab=E3}
N 150 -150 150 -70 {lab=VSS}
N 50 -150 50 -70 {lab=VSS}
N 50 -70 150 -70 {lab=VSS}
N 690 -600 1110 -600 {lab=OUTI}
N 180 -470 260 -470 {lab=E9}
N 1110 -610 1110 -600 {lab=OUTI}
N 860 -380 1110 -380 {lab=SB}
N 860 -700 1110 -700 {lab=SA}
N 1240 -1120 1240 -960 {lab=VBOOST}
N 1110 -410 1110 -380 {lab=SB}
N 1110 -730 1110 -700 {lab=SA}
N 860 -760 1070 -760 {lab=GA}
N 340 -740 340 -690 {lab=C2}
N 340 -630 340 -560 {lab=C9}
N 220 -630 340 -630 {lab=C9}
N 180 -600 180 -560 {lab=C5}
N 1110 -320 1110 -280 {lab=VNN}
N 1330 -590 1390 -590 {lab=OUT}
N 1110 -590 1240 -590 {lab=OUTI}
N 1110 -600 1110 -590 {lab=OUTI}
N 340 -860 340 -820 {lab=#net4}
N 560 -860 560 -820 {lab=#net5}
N 560 -1020 560 -920 {lab=E6}
N 340 -1020 340 -920 {lab=E2}
N 260 -280 260 -240 {lab=C3}
N 730 -440 770 -440 {lab=#net6}
N 560 -440 670 -440 {lab=C8}
N 690 -650 690 -600 {lab=OUTI}
N 690 -730 690 -710 {lab=#net7}
N 180 -840 180 -660 {lab=C7}
N 840 -860 840 -840 {lab=E11}
N 1240 -810 1240 -590 {lab=OUTI}
N 860 -760 860 -750 {lab=GA}
N 860 -710 860 -700 {lab=SA}
N 860 -440 860 -430 {lab=GB}
N 860 -390 860 -380 {lab=SB}
N 1240 -590 1270 -590 {lab=OUTI}
N 830 -440 860 -440 {lab=GB}
N 840 -760 860 -760 {lab=GA}
N 340 -1180 340 -1080 { lab=VPP}
N 560 -1180 560 -1080 { lab=VPP}
N 60 -1180 340 -1180 {lab=VPP}
N 340 -1180 560 -1180 {lab=VPP}
N 1110 -1180 1110 -790 { lab=VPP}
N 560 -1180 1110 -1180 {lab=VPP}
N 230 -950 800 -950 { lab=#net2}
C {ipin.sym} 530 -160 0 0 {name=p0 lab=PLUS}
C {ipin.sym} 530 -120 0 0 {name=p2 lab=VPP}
C {ipin.sym} 530 -100 0 0 {name=p3 lab=VNN}
C {nmos3.sym} 1090 -440 0 0 {name=xm2 model=irf540 m=1
program=evince
url="https://www.vishay.com/docs/91021/91021.pdf"
 net_name=true}
C {res.sym} 960 -410 0 1 {name=R7 m=1 value=190 net_name=true}
C {nmos3.sym} 1090 -760 0 0 {name=xm1 model=irf540 m=1
program=evince
url="https://www.vishay.com/docs/91021/91021.pdf" net_name=true}
C {res.sym} 960 -730 0 1 {name=R0 m=1 value=190 net_name=true}
C {lab_pin.sym} 1390 -590 0 1 {name=p14 lab=OUT}
C {lab_pin.sym} 1110 -280 0 0 {name=p18 lab=VNN}
C {lab_wire.sym} 920 -440 0 0 {name=l8 lab=GB}
C {res.sym} 340 -1050 0 1 {name=R2 m=1 value=50 net_name=true}
C {res.sym} 180 -1050 0 1 {name=R3 m=1 value=50 net_name=true}
C {lab_pin.sym} 340 -1080 0 0 {name=p10 lab=VPP}
C {npn.sym} 160 -530 0 0 {name=Q5 model=q2n2222 area=1 net_name=true}
C {pnp.sym} 820 -950 0 0 {name=Q4 model=q2n2907p area=1 net_name=true}
C {res.sym} 840 -1050 0 1 {name=R9 m=1 value=50 net_name=true}
C {pnp.sym} 540 -790 0 0 {name=Q6 model=q2n2907p area=1 net_name=true}
C {res.sym} 560 -1050 0 1 {name=R4 m=1 value=50 net_name=true}
C {lab_pin.sym} 180 -580 0 0 {name=p15 lab=C5}
C {lab_pin.sym} 340 -580 0 1 {name=p16 lab=C9}
C {lab_pin.sym} 180 -1000 0 0 {name=p17 lab=E1}
C {lab_pin.sym} 560 -1080 0 0 {name=p25 lab=VPP}
C {lab_pin.sym} 340 -970 0 1 {name=p23 lab=E2}
C {lab_pin.sym} 560 -970 0 1 {name=p28 lab=E6}
C {lab_pin.sym} 840 -1000 0 0 {name=p29 lab=E4}
C {lab_pin.sym} 180 -1120 0 0 {name=p34 lab=VBOOST}
C {ammeter.sym} 1110 -540 0 0 {name=vd  net_name=true current=0.2069}
C {ammeter.sym} 1110 -640 0 0 {name=vu  net_name=true current=0.2005}
C {lab_pin.sym} 60 -1180 0 0 {name=p27 lab=VPP}
C {pnp.sym} 200 -950 0 1 {name=Q1 model=q2n2907p area=1 net_name=true}
C {pnp.sym} 360 -790 0 1 {name=Q2 model=q2n2907p area=1 net_name=true}
C {lab_pin.sym} 140 -530 0 0 {name=p6 lab=PLUS}
C {lab_pin.sym} 380 -530 0 1 {name=p24 lab=MINUS}
C {npn.sym} 360 -530 0 1 {name=Q9 model=q2n2222 area=1 net_name=true}
C {lab_pin.sym} 560 -670 0 0 {name=p9 lab=C6}
C {code.sym} 1040 -180 0 0 {name=STIMULI
only_toplevel=true
value=".option PARHIER=LOCAL RUNLVL=6 post MODMONTE=1 warn maxwarn=6000
.option sampling_method = SRS ingold=1
.option method=gear
.option savecurrents
.temp 30



vvss vss 0 dc 0 
vvpp vpp 0 dc 50
vvnn vnn 0 dc -50

rfb1 vpp minus 100k
rfb2 out minus 100k
rfb3 minus vdc '100k/43'


vvdc vdc 0 dc 21.3
eref vref 0 plus vdc 45

vplus plus vdc dc 0

evboost vboost 0 vol='v(out)>=40 ? v(out)+10 : 50'
rload out 0 4

** models are generally not free: you must download
** SPICE models for active devices and put them  into the below 
** referenced file in simulation directory.
.include \\"models_poweramp.txt\\"
.dc vplus '-1.5' '1.5' 0.1
.save all
.op
*.probe dc v(plus,vdc)
"}
C {lab_wire.sym} 920 -760 0 0 {name=l1 lab=GA}
C {res.sym} 800 -440 1 1 {name=R11 m=1 value=1300 net_name=true}
C {pnp.sym} 540 -490 0 0 {name=Q8 model=q2n2907p area=1 net_name=true}
C {capa.sym} 1240 -930 0 0 {name=C12 m=1 value="40u" net_name=true}
C {diode.sym} 1240 -1150 0 0 {name=D0 model=d1n4148 area=1
url="http://pdf.datasheetcatalog.com/datasheet/bytes/1N5406.pdf" net_name=true}
C {res.sym} 1240 -840 0 1 {name=R18 m=1 value=200 net_name=true}
C {zener.sym} 1400 -1150 0 0 {name=D1 model=d1n758 area=1
url="http://www.futurlec.com/Datasheet/Diodes/1N746-1N759.pdf" net_name=true}
C {res.sym} 690 -760 0 1 {name=R14 m=1 value=4k net_name=true}
C {pnp.sym} 820 -810 0 0 {name=Q11 model=q2n2907p area=1 net_name=true}
C {res.sym} 690 -850 0 1 {name=R15 m=1 value=4k net_name=true}
C {res.sym} 260 -430 0 1 {name=R5 m=1 value=120 net_name=true}
C {res.sym} 260 -370 0 1 {name=R6 m=1 value=120 net_name=true}
C {zener.sym} 150 -180 2 0 {name=D2 model=d1n755 area=1
url="http://www.futurlec.com/Datasheet/Diodes/1N746-1N759.pdf"
 net_name=true}
C {npn.sym} 240 -210 0 0 {name=Q3 model=q2n2222 area=1 net_name=true}
C {res.sym} 150 -240 0 1 {name=R1 m=1 value=10k net_name=true}
C {lab_pin.sym} 150 -270 0 0 {name=p7 lab=VPP}
C {res.sym} 260 -100 0 1 {name=R10 m=1 value=170 net_name=true}
C {lab_pin.sym} 50 -70 0 0 {name=p11 lab=VSS}
C {capa.sym} 50 -180 0 0 {name=C3 m=1 value=100n net_name=true}
C {res.sym} 560 -610 0 1 {name=R12 m=1 value=1300 net_name=true}
C {lab_pin.sym} 690 -800 0 0 {name=p12 lab=B1}
C {lab_pin.sym} 340 -470 0 1 {name=p13 lab=E9}
C {lab_pin.sym} 560 -440 0 0 {name=p19 lab=C8}
C {lab_pin.sym} 560 -560 0 1 {name=p20 lab=E8}
C {lab_pin.sym} 840 -850 0 0 {name=p21 lab=E11}
C {lab_pin.sym} 260 -160 0 1 {name=p22 lab=E3}
C {lab_pin.sym} 260 -270 0 0 {name=p26 lab=C3}
C {lab_pin.sym} 50 -210 0 0 {name=p30 lab=B3}
C {lab_pin.sym} 520 -490 0 0 {name=p33 lab=VSS}
C {res.sym} 340 -660 0 1 {name=R13 m=1 value=300 net_name=true}
C {npn.sym} 200 -630 0 1 {name=Q7 model=q2n2222 area=1 net_name=true}
C {lab_pin.sym} 180 -690 0 0 {name=p8 lab=C7}
C {lab_pin.sym} 340 -710 0 1 {name=p31 lab=C2}
C {title.sym} 160 -30 0 0 {name=l2 author="Stefan Schippers"}
C {lab_pin.sym} 860 -700 0 0 {name=p32 lab=SA}
C {ammeter.sym} 1110 -350 0 0 {name=v0  net_name=true current=0.2263}
C {lab_pin.sym} 860 -380 0 0 {name=p35 lab=SB}
C {ammeter.sym} 560 -890 0 0 {name=v1  net_name=true current=0.01956}
C {ammeter.sym} 340 -890 0 0 {name=v2  net_name=true current=0.01947}
C {ammeter.sym} 260 -310 0 0 {name=v3  net_name=true current=0.03918}
C {ammeter.sym} 700 -440 3 0 {name=v4  net_name=true current=0.01941}
C {ammeter.sym} 690 -680 0 0 {name=v5  net_name=true current=0.006184}
C {ammeter.sym} 180 -870 0 1 {name=v6  net_name=true current=0.01949}
C {ammeter.sym} 840 -890 0 0 {name=v7  net_name=true current=0.01944}
C {spice_probe_vdiff.sym} 860 -410 0 0 {name=p37 voltage=3.688}
C {spice_probe_vdiff.sym} 860 -730 0 0 {name=p38 voltage=3.68}
C {ammeter.sym} 1300 -590 3 0 {name=v8  net_name=true current=-2.1216e-04}
C {opin.sym} 600 -130 0 0 {name=p5 lab=OUT}
C {ipin.sym} 530 -180 0 0 {name=p1 lab=MINUS}
C {ipin.sym} 530 -140 0 0 {name=p4 lab=VSS}
C {launcher.sym} 510 -330 0 0 {name=h2
descr="Ctrl-Click
Clear all probes" 
tclcommand="
    xschem push_undo
    xschem set no_undo 1
    xschem set no_draw 1
 
    set lastinst [xschem get instances]
    for \{ set i 0 \} \{ $i < $lastinst \} \{incr i \} \{
      set type [xschem getprop instance $i cell::type]
      if \{ [regexp \{(^|/)probe$\} $type ] \} \{
        xschem setprop $i voltage fast
      \}
      if \{ [regexp \{current_probe$\} $type ] \} \{
        xschem setprop $i current fast
      \}
      if \{ [regexp \{differential_probe$\} $type ] \} \{
        xschem setprop $i voltage fast
      \}
    \}
    xschem set no_undo 0
    xschem set no_draw 0
    xschem redraw
"
}
C {ngspice_probe.sym} 750 -1120 0 0 {name=p54}
C {ngspice_probe.sym} 180 -760 0 0 {name=p53}
C {ngspice_probe.sym} 560 -710 0 0 {name=p55}
C {ngspice_get_value.sym} 1130 -780 0 0 {name=nmos1 node=i(@r.$\{path\}xm1.rd[i])
descr="Id="}
C {ngspice_get_expr.sym} 800 -1000 0 1 {name=r8 
node="[format %.4g [expr [ngspice::get_voltage e4] - [ngspice::get_voltage c7]]]"
descr = veb
}
C {ngspice_get_expr.sym} 860 -980 0 0 {name=r9 
node="[format %.4g [expr [ngspice::get_current \{q4[ic]\}] / [ngspice::get_current \{q4[ib]\}] ] ]"
descr = beta
}
C {ngspice_probe.sym} 560 -830 0 0 {name=p41}
C {ngspice_probe.sym} 560 -530 0 1 {name=p42}
C {ngspice_probe.sym} 590 -440 2 1 {name=p47}
C {ngspice_get_expr.sym} 860 -920 0 0 {name=r15 
node="[format %.4g [expr ([ngspice::get_voltage e4] - [ngspice::get_voltage e11]) * [ngspice::get_current \{q4[ic]\}]]] W"
descr = power
}
C {ngspice_probe.sym} 260 -260 0 0 {name=p48}
C {ngspice_probe.sym} 90 -70 0 0 {name=p49}
C {ngspice_probe.sym} 100 -210 0 1 {name=p52}
C {ngspice_probe.sym} 1190 -590 0 1 {name=p39}
C {ngspice_probe.sym} 890 -700 2 1 {name=p43}
C {ngspice_probe.sym} 460 -790 2 1 {name=p44}
C {ngspice_probe.sym} 730 -810 2 1 {name=p46}
C {ngspice_probe.sym} 440 -950 0 0 {name=p50}
C {ngspice_probe.sym} 200 -470 0 0 {name=p45}
C {ngspice_probe.sym} 340 -600 0 0 {name=p51}
C {ngspice_get_expr.sym} 330 -900 0 1 {name=r17 
node="[ngspice::get_current v2]" 
descr = current
}
C {ngspice_get_expr.sym} 360 -1040 0 0 {name=r18 
node="[ngspice::get_current \{r2[i]\}]"
descr = current
}
C {ngspice_get_expr.sym} 860 -1040 0 0 {name=r19 
node="[ngspice::get_current \{r9[i]\}]"
descr = current
}
C {ngspice_get_expr.sym} 820 -890 0 1 {name=r2 
node="[ngspice::get_current \{q4[ic]\}]"
descr = current
}
C {ngspice_get_expr.sym} 800 -970 0 1 {name=r1 
node="[ngspice::get_current \{q4[ib]\}]"
descr = Ib
}
C {ngspice_get_expr.sym} 580 -460 0 0 {name=r11 
node="[format %.4g [expr ([ngspice::get_voltage e8] - [ngspice::get_voltage c8]) * [ngspice::get_current \{q8[ic]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 190 -860 0 0 {name=r12 
node="[ngspice::get_current v6]" 
descr = current
}
C {ngspice_get_expr.sym} 240 -210 0 1 {name=r6 
node="[format %.4g [expr [ngspice::get_current \{q3[ic]\}] / [ngspice::get_current \{q3[ib]\}] ] ]"
descr = beta
}
C {ngspice_get_expr.sym} 860 -780 0 0 {name=r16 
node="[format %.4g [expr ([ngspice::get_voltage e11] - [ngspice::get_voltage ga]) * [ngspice::get_current \{q11[ic]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 980 -720 0 0 {name=r20 
node="[ngspice::get_current \{r0[i]\}]" 
descr = current
}
C {ngspice_get_expr.sym} 280 -200 2 1 {name=r3 
node="[format %.4g [expr ([ngspice::get_voltage c3] - [ngspice::get_voltage e3]) * [ngspice::get_current \{q3[ic]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 240 -190 2 0 {name=r21 
node="[format %.4g [expr [ngspice::get_voltage b3] - [ngspice::get_voltage e3]]]"
descr = vbe
}
C {ngspice_get_expr.sym} 340 -390 0 0 {name=r7 
node="[format %.4g [expr ([ngspice::get_voltage e9] - [ngspice::get_voltage c3]) * [ngspice::get_current \{r5[i]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 570 -760 0 0 {name=r10 
node="[format %.4g [expr ([ngspice::get_voltage e6] - [ngspice::get_voltage c6]) * [ngspice::get_current \{q6[ic]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 210 -650 0 0 {name=r14 
node="[format %.4g [expr ([ngspice::get_voltage c7] - [ngspice::get_voltage c5]) * [ngspice::get_current \{q7[ic]\}]]]"
descr = power
}
C {ngspice_probe.sym} 180 -560 0 0 {name=p36}
C {ngspice_get_expr.sym} 200 -500 0 0 {name=r13 
node="[format %.4g [expr ([ngspice::get_voltage c5] - [ngspice::get_voltage e9]) * [ngspice::get_current \{q5[ic]\}]]]"
descr = power
}
C {ngspice_get_expr.sym} 320 -500 0 1 {name=r22 
node="[format %.4g [expr ([ngspice::get_voltage c9] - [ngspice::get_voltage e9]) * [ngspice::get_current \{q9[ic]\}]]]"
descr = power
}
C {ngspice_get_expr.sym} 330 -760 0 1 {name=r23 
node="[format %.4g [expr [ngspice::get_current \{q2[ic]\}] / [ngspice::get_current \{q2[ib]\}] ] ]"
descr = beta
}
C {ngspice_get_expr.sym} 1090 -640 0 1 {name=r24 
node="[ngspice::get_current vu]" 
descr = current
}
C {ngspice_get_expr.sym} 1090 -530 0 1 {name=r25 
node="[ngspice::get_current vd]" 
descr = current
}
C {ngspice_get_expr.sym} 1210 -1140 0 1 {name=r5 
node="[ngspice::get_current \{d0[id]\}]"
descr = current
}
C {ngspice_get_expr.sym} 1370 -1150 0 1 {name=r26 
node="[ngspice::get_current \{d1[id]\}]"
descr = current
}
C {ngspice_get_value.sym} 1130 -460 0 0 {name=r27 node=i(@r.$\{path\}xm2.rd[i])
descr="Id="}
C {ngspice_get_expr.sym} 160 -230 0 0 {name=r28 
node="[format %.4g [expr ([ngspice::get_node v(vpp)] - [ngspice::get_voltage b3]) * [ngspice::get_current \{r1[i]\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 1130 -740 2 1 {name=r29 
node="[format %.4g [expr ([ngspice::get_node v(vpp)] - [ngspice::get_voltage outi]) * [ngspice::get_current \{vu\}]]] W"
descr = power
}
C {lab_wire.sym} 910 -600 0 1 {name=l40 lab=OUTI}
C {ngspice_get_expr.sym} 980 -400 0 0 {name=r30 
node="[ngspice::get_current \{r7[i]\}]" 
descr = current
}
C {ngspice_get_expr.sym} 700 -440 2 0 {name=r31 
node="[ngspice::get_current \{v4\}]" 
descr = current
}
C {ngspice_get_expr.sym} 1130 -420 2 1 {name=r32 
node="[format %.4g [expr ([ngspice::get_voltage outi] - [ngspice::get_node v(vnn)]) * [ngspice::get_current \{vd\}]]] W"
descr = power
}
C {ngspice_get_expr.sym} 150 -160 2 0 {name=r33 
node="[format %.4g [expr -[ngspice::get_voltage b3] * [ngspice::get_current \{d2[id]\}]]] W"
descr = power
}
C {launcher.sym} 770 -70 0 0 {name=h3
descr="Load file into gaw" 
comment="
  This launcher gets raw filename from current schematic using 'xschem get schname'
  and stripping off path and suffix.  It then loads raw file into gaw.
  This allow to use it in any schematic without changes.
"
tclcommand="
set rawfile [file tail [file rootname [xschem get schname]]].raw
gaw_cmd \\"tabledel $rawfile
load $netlist_dir/$rawfile
table_set $rawfile\\"
unset rawfile"
}
C {spice_probe.sym} 1010 -760 0 0 {name=p40  voltage=3.543}
C {spice_probe.sym} 1000 -440 0 0 {name=p56  voltage=-46.18}
C {spice_probe.sym} 420 -790 0 0 {name=p57 voltage=48.06}
C {spice_probe.sym} 280 -950 0 0 {name=p58  voltage=47.27}
C {spice_probe.sym} 180 -720 0 0 {name=p59  voltage=47.27}
C {spice_probe.sym} 1020 -1120 0 0 {name=p62  voltage=49.04}
C {launcher.sym} 770 -110 0 0 {name=h1
descr=Backannotate
tclcommand="ngspice::annotate"}
C {launcher.sym} 770 -150 0 0 {name=h4
descr="View Raw file" 
tclcommand="textwindow $netlist_dir/[file tail [file rootname [ xschem get schname 0 ] ] ].raw"
}
C {spice_probe.sym} 790 -600 0 0 {name=p60 analysis=tran voltage=-0.1364}