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On the Computational Power of Spiking Neural P Systems

Abstract

In this paper we study some computational properties of spiking neural P systems. In particular, we show that by using nondeterminism in a slightly extended version of spiking neural P systems it is possible to solve in constant time both the numerical NP-complete problem Subset Sum and the strongly NP-complete problem 3-SAT. Then, we show how to simulate a universal deterministic spiking neural P system with a deterministic Turing machine, in a time which is polynomial with respect to the execution time of the simulated system. Surprisingly, it turns out that the simulation can be performed in polynomial time with respect to the size of the description of the simulated system only if the regular expressions used in such a system are of a very restricted type.

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On the Computational Power of Spiking Neural P Systems

Author: Leporati, Alberto; Zandron, Claudio; Ferretti, Claudio; Mauri, Giancarlo
Publisher: Fénix Editora
Year: 2007
Source: https://idus.us.es/bitstreams/a403040c-3358-4625-b0ec-66dcb07ea79e/download
On he Compu a ional Powe
o Spiking Neu al P Sys ems
Albe o Lepo a i, Claudio Zand on,
Claudio Fe e i, Gianca lo Mau i
Dipa imen o di In o ma ica, Sis emis ica e Comunicazione
Uni e si `a degli S udi di Milano – Bicocca
Via Bicocca degli A cimboldi 8, 20126 Milano, I aly
{lepo a i,zand on, e e i,mau i}@disco.unimib.i
Summa y. In his pape we s udy some compu a ional p ope ies o spiking neu al P
sys ems. In pa icula , we show ha by using nonde e minism in a sligh ly ex ended
e sion o spiking neu al P sys ems i is possible o sol e in cons an ime bo h he
nume ical NP–comple e p oblem Subse Sum and he s ongly NP–comple e p oblem
3-SAT. Then, we show how o simula e a uni e sal de e minis ic spiking neu al P sys em
wi h a de e minis ic Tu ing machine, in a ime which is polynomial wi h espec o he
execu ion ime o he simula ed sys em. Su p isingly, i u ns ou ha he simula ion
can be pe o med in polynomial ime wi h espec o he size o he desc ip ion o he
simula ed sys em only i he egula exp essions used in such a sys em a e o a e y
es ic ed ype.
1 In oduc ion
Memb ane sys ems (also called P sys ems) we e in oduced in [16] as a new class o
dis ibu ed and pa allel compu ing de ices, inspi ed by he s uc u e and unc ion-
ing o li ing cells. The basic model consis s o a hie a chical s uc u e composed by
se e al memb anes, embedded in o a main memb ane called he skin. Memb anes
di ide he Euclidean space in o egions, ha con ain some objec s ( ep esen ed
by symbols o an alphabe ) and e olu ion ules. Using hese ules, he objec s
may e ol e and/o mo e om a egion o a neighbo ing one. Usually, he ules
a e applied in a nonde e minis ic and maximally pa allel way; mo eo e , all he
objec s ha may e ol e a e o ced o e ol e. A compu a ion s a s om an ini ial
con igu a ion o he sys em and e mina es when no e olu ion ule can be applied.
The esul o a compu a ion is he mul ise o objec s con ained in o an ou pu
memb ane, o emi ed om he skin o he sys em. Fo a sys ema ic in oduc ion
o P sys ems we e e he eade o [18], whe eas he la es in o ma ion can be
ound in [23].
228 A. Lepo a i e al.
In an a emp o pass om cell-like o issue-like a chi ec u es, in [13] issue
P sys ems we e de ined, in which cells a e placed in he nodes o a (di ec ed)
g aph. Since hen, his model has been u he elabo a ed, o example, in [4]
and [19], wi h ecen esul s abou bo h heo e ical p ope ies [1] and applica ions
[14]. This e olu ion has led o explo e also neu al-like a chi ec u es, yielding o
he in oduc ion o spiking neu al P sys ems (SN P sys ems, o sho ) [8], based
on he neu ophysiological beha io o neu ons sending elec ical impulses (spikes)
along axons o o he neu ons. We ecall ha his biological backg ound has al eady
led o se e al models in he a ea o neu al compu a ion, e.g., see [11, 12, 6].
Simila ly o issue P sys ems, in SN P sys ems he cells (neu ons) a e placed
in he nodes o a di ec ed g aph, called he synapse g aph. The con en s o each
neu on consis o a numbe o copies o a single objec ype, called he spike. The
i ing ules assigned o a cell allow a neu on o send in o ma ion o o he neu ons
in he o m o elec ical impulses (also called spikes) which a e accumula ed a he
a ge cell. The applica ion o he ules depends on he con en s o he neu on;
in he gene al case, applicabili y is de e mined by checking he con en s o he
neu on agains a egula se associa ed wi h he ule. As inspi ed om biology,
a e a cell sends ou spikes i becomes “closed” (inac i e) o a speci ied pe iod o
ime, ha e lec s he e ac o y pe iod o biological neu ons. Du ing his pe iod,
he neu on does no accep new inpu s and canno “ i e” ( ha is, emi spikes).
Ano he impo an ea u e o biological neu ons is ha he leng h o he axon
may cause a ime delay be o e a spike a i es a he a ge . In SN P sys ems his
delay is modeled by associa ing a delay pa ame e o each ule which occu s in he
sys em. I no i ing ule can be applied in a neu on, he e may be he possibili y
o apply a o ge ing ule, ha emo es om he neu on a p ede ined numbe o
spikes.
In he o iginal model o SN P sys ems de ined in [8], compu a ions occu as
ollows. A con igu a ion speci ies, o each neu on o he sys em, he numbe o
spikes i con ains and he numbe o compu a ion s eps a e which he neu on
will become “open” ( ha is, no closed). S a ing om an ini ial con igu a ion, a
posi i e in ege numbe is gi en in inpu o a speci ied inpu neu on. The numbe
is encoded as he in e al o ime s eps elapsed be ween he inse ion o wo spikes
in o he neu on. To pass om a con igu a ion o ano he one, o each neu on a
ule is chosen among he se o applicable ules, and is execu ed. The compu a ion
p oceeds in a sequen ial way in o each neu on, and in pa allel among di e en
neu ons. Gene ally, a compu a ion may no hal . Howe e , in any case he ou pu
o he sys em is conside ed o be he ime elapsed be ween he a i al o wo
spikes in a designa ed ou pu cell. De ined in his way, SN P sys ems compu e
unc ions o he kind :N→N( hey can also indi ec ly compu e unc ions o
he kind :Nk→Nby using a bijec ion om Nk o N). By igno ing he ou pu
neu on we can de ine accep ing SN P sys ems, in which he na u al numbe gi en
in inpu is accep ed i he compu a ion hal s, and ejec ed o he wise. On he o he
hand, by igno ing he inpu neu on (and hus s a ing om a p ede ined inpu
con igu a ion) we can de ine gene a i e SN P sys ems.
On he Compu a ional Powe o SN P Sys ems 229
In [8] i was shown ha gene a i e SN P sys ems a e uni e sal, ha is, can
gene a e any ecu si ely enume able se o na u al numbe s. Mo eo e , a cha -
ac e iza ion o semilinea se s was ob ained by spiking neu al P sys ems wi h a
bounded numbe o spikes in he neu ons. These esul s can also be ob ained wi h
e en mo e es ic ed o ms o spiking P sys ems; o example, [7] shows ha a
leas one o hese ea u es can be a oided while keeping uni e sali y: ime delay
( e ac o y pe iod) g ea e han 0, o ge ing ules, ou deg ee o he synapse g aph
g ea e han 2, and egula exp essions o complex o m. Finally, in [20] he be-
ha io o spiking neu al P sys ems on in ini e s ings and he gene a ion o in ini e
sequences o 0 and 1 was in es iga ed, whe eas in [2] spiking neu al P sys ems
we e s udied as language gene a o s (o e he bina y alphabe {0,1}).
The es o his pape is o ganized as ollows. In sec ion 2 we gi e some ma h-
ema ical p elimina ies, and we de ine he s anda d e sion o SN P sys ems (as
ound in [9]) as well as a sligh ly ex ended e sion. In sec ion 3 we show how he
NP–comple e p oblems Subse Sum and 3-SAT can be sol ed in cons an ime
by exploi ing nonde e minism in ou ex ended SN P sys ems. In sec ion 4 we u n
ou a en ion o de e minis ic sys ems, and we show how o simula e hem by us-
ing de e minis ic Tu ing machines. Sec ion 5 concludes he pape and gi es some
di ec ions o u u e esea ch.
2 P elimina ies
Le us s a by ecalling he s anda d de ini ion o a spiking neu al P sys em, aken
om [9]. A spiking neu al memb ane sys em (SN P sys em, o sho ), o deg ee
m≥1, is a cons uc o he o m
Π= (O, σ1, σ2,...,σm, syn, in, ou ),
whe e:
1. O={a}is he single on alphabe (ais called spike);
2. σ1, σ2,...,σma e neu ons, o he o m σi= (ni, Ri), wi h 1 ≤i≤m, whe e:
a) ni≥0 is he ini ial numbe o spikes con ained in σi;
b) Riis a ini e se o ules o he ollowing wo o ms:
(1) E/ac→a;d, whe e Eis a egula exp ession o e a, and c≥1, d≥0
a e in ege numbe s; i E=ac, hen i is usually w i en in he ollowing
simpli ied o m: ac→a;d;
(2) as→λ, o s≥1, wi h he es ic ion ha o each ule E/ac→a;do
ype (1) om Ri, we ha e as6∈ L(E) (whe e L(E) deno es he egula
language de ined by E);
3. syn ⊆ {1,2,...,m} × {1,2,...,m}, wi h (i, i)6∈ syn o 1 ≤i≤m, is he
di ec ed g aph o synapses be ween neu ons;
4. in, ou ∈ {1,2,...,m}indica e he inpu and he ou pu neu ons o Π.
230 A. Lepo a i e al.
The ules o ype (1) a e called i ing (also spiking) ules, and hey a e applied
as ollows. I he neu on σicon ains k≥cspikes, and ak∈L(E), hen he ule
E/ac→a;d∈Rican be applied. The execu ion o his ule emo es cspikes om
σi( hus lea ing k−cspikes), and p epa es one spike o be deli e ed o all he
neu ons σjsuch ha (i, j)∈syn. I d= 0, hen he spike is immedia ely emi ed,
o he whise i is emi ed a ed dcompu a ion s eps o he sys em. (Obse e ha , as
usually happens in memb ane compu ing, a global clock is assumed, ma king he
ime o he whole sys em, hence he unc ioning o he sys em is synch onized.)
I he ule is used in s ep and d≥1, hen in s eps , + 1, + 2, . . . , +d−1 he
neu on is closed, so ha i canno ecei e new spikes (i a neu on has a synapse
o a closed neu on and ies o send a spike along i , hen ha pa icula spike is
los ), and canno i e new ules. In he s ep +d, he neu on spikes and becomes
again open, so ha i can ecei e spikes (which can be used s a ing wi h he s ep
+d+ 1) and selec ules o be i ed.
Rules o ype (2) a e called o ge ing ules, and a e applied as ollows: i he
neu on σicon ains exac ly sspikes, hen he ule as→λ om Rican be used,
meaning ha all sspikes a e emo ed om σi. No e ha , by de ini ion, i a i ing
ule is applicable, hen no o ge ing ule is applicable, and ice e sa.
In each ime uni , i a neu on σican use one o i s ules, hen a ule om Ri
mus be used. Since wo i ing ules, E1:ac1→a;d1and E2:ac1→a;d2, can
ha e L(E1)∩L(E2)6=∅, i is possible ha wo o mo e ules can be applied in a
neu on. In such a case, only one o hem is chosen nonde e minis ically. Thus, he
ules a e used in he sequen ial manne in each neu on, bu neu ons unc ion in
pa allel wi h each o he .
The ini ial con igu a ion o he sys em is desc ibed by he numbe s n1, n2, . . .,
nmo spikes p esen in each neu on, wi h all neu ons being open. Du ing he
compu a ion, a con igu a ion is desc ibed by bo h he numbe o spikes p esen
in each neu on and by he s a e o each neu on, which can be exp essed as he
numbe o s eps o coun down un il i becomes open ( his numbe is ze o i
he neu on is al eady open). A compu a ion in a sys em as abo e s a s in he
ini ial con igu a ion. In o de o compu e a unc ion :Nk→N, we in oduce k
na u al numbe s n1, n2,...,nkin he sys em by “ eading” om he en i onmen
a bina y sequence z= 0b10n110n21...10nk10g, o some b, g ≥0; his means ha
he inpu neu on o Π ecei es a spike in each s ep co esponding o a digi 1
om he s ing z. No e ha we inpu exac ly k+ 1 spikes. The esul o he
compu a ion is also encoded in he dis ance be ween wo spikes: we impose o he
sys em o ou pu exac ly wo spikes and hal (some imes a e he second spike)
hence p oducing a ain spike o he o m 0b010 10g0, o some b0, g0≥0 and wi h
= (n1, n2,...,nk).
I we use an SN P sys em in he gene a i e mode, hen no inpu neu on is
conside ed, hence no inpu is aken om he en i onmen ; we s a om he ini ial
con igu a ion, and he dis ance be ween he i s wo spikes o he ou pu neu on
(o o he numbe s, see he discussion in [9]) is he esul o he compu a ion.
On he Compu a ional Powe o SN P Sys ems 231
Dually, we can igno e he ou pu neu on, and i he compu a ion hal s, hen he
numbe is accep ed.
We de ine he desc ip ion size o an SN P sys em Πas he numbe o bi s which
a e necessa y o desc ibe i . Since he alphabe Ois ixed, no bi s a e necessa y
o de ine i . In o de o ep esen syn we need a mos m2bi s, whe eas we can
ep esen he alues o in and ou by using log mbi s each. E e y neu on σi equi es
o speci y a na u al numbe ni, and a se Rio ules. Each ule equi es o speci y
i s ype ( i ing o o ge ing), which can be done wi h 1 bi , and in he wo s case
i equi es o speci y a egula exp ession and wo na u al numbe s. I we deno e
by N he maximum na u al numbe ha appea s in he de ini ion o Π,R he
maximum numbe o ules which occu in i s neu ons, and S he maximum size
equi ed by he egula exp essions ha occu in Π(mo e on his la e ), hen we
need a maximum o log N+R(1+S+ 2 log N) bi s o desc ibe e e y neu on o Π.
Hence, o desc ibe Πwe need a o al o m2+2 log m+mlog N+R(1+S+2 logN)
bi s. No e ha his quan i y is polynomial wi h espec o m,R,Sand log N.
Since he egula languages de e mined by he egula exp essions ha occu in
he sys em a e una y languages, he s ings o such languages can be bijec i ely
iden i ied by hei leng hs. Hence, when w i ing he egula exp ession E, ins ead
o w i ing unions, conca ena ions and Kleene closu es among s ings we can do he
same by using he leng hs o such s ings. In his way we ob ain a ep esen a ion
o Ewhich is exponen ially mo e compac han he usual ep esen a ion o egula
exp essions. As we will see in sec ion 4, his compac ep esen a ion will yield
some di icul ies when we will simula e a de e minis ic accep ing SN P sys em by
a de e minis ic Tu ing machine.
In wha ollows i will be con enien o conside also a sligh ly ex ended e sion
o SN P sys ems. P ecisely, we will allow ules o he ype E/ac→ap;d, whe e
c≥1, p≥0 and d≥0 a e in ege numbe s. The seman ics o his kind o ules
is as ollows: i he con en s o he neu on ma ches he egula exp ession E, hen
he ule can be applied. When he ule is applied, cspikes a e emo ed om he
con en s o he neu on and pspikes a e p epa ed o be deli e ed o all he neu ons
which a e di ec ly connec ed ( h ough an a c o syn) wi h he cu en neu on. I
d= 0, hen hese pspikes a e immedia ely sen , o he wise he neu on becomes
closed o he nex dcompu a ion s eps, a e which he pspikes will be sen . As
be o e, a closed neu on does no ecei e spikes om o he neu ons, and does no
apply any ule. I p= 0, hen we ob ain a o ge ing ule as a pa icula case o
ou gene al ules.
Also in he ex ended SN P sys ems i may happen ha , gi en wo ules
E1/ac1→ap1;d1and E2/ac2→ap2;d2, i L(E1)∩L(E2)6=∅ hen o some con-
en s o he neu on bo h he ules can be applied. In such a case, we nonde e min-
is ically choose one o hem. No e ha we do no equi e ha o ge ing ules a e
applied only when no i ing ule can be applied. We say ha he sys em is de e min-
is ic i , o e e y neu on ha occu s in he sys em, any wo ules E1/ac1→ap1;d1
and E2/ac2→ap2;d2in he neu on a e such ha L(E1)∩L(E2) = ∅. This means

232 A. Lepo a i e al.
ha , o any possible con en s o he neu on, a mos one o he ules ha occu
in he neu on may be applied.
By using an inpu neu on and an ou pu neu on, we ha e SN P sys ems ha
compu e unc ions o he kind :N→N, and hence we co e bo h he gene a i e
and he accep ing cases. I ou = 0, hen i is unde s ood ha he ou pu is sen
o he en i onmen (as he numbe o spikes p oduced by he sys em, as he dis-
ance be ween he i s wo spikes, e c.). As usual, o use an SN P sys em in he
gene a i e mode we do no conside he inpu neu on, and hus no inpu is aken
om he en i onmen ; we s a om he ini ial con igu a ion, and he dis ance
be ween he i s wo spikes o he ou pu neu on (o he numbe o spikes con-
ained in o he ou pu neu on a he end o he compu a ion, as discussed abo e)
is he esul o he compu a ion. No e ha gene a i e SN P sys ems a e inhe en ly
nonde e minis ic, o he wise hey would always ep oduce he same sequence o
compu a ion s eps, and hence he same ou pu . Dually, we can igno e he ou pu
neu on o ob ain an accep ing SN P sys em. We inpu a numbe in he sys em as
he dis ance be ween wo spikes en e ing he inpu neu on (o he numbe o spikes
ha occu in he inpu neu on in he ini ial con igu a ion) and, i he compu a ion
hal s, hen he numbe is accep ed.
The desc ip ion size o an ex ended SN P sys em is de ined exac ly as we did
o s anda d sys ems, he only di e ence being ha now we equi e (a mos ) h ee
na u al numbe s o desc ibe a ule.
3 Sol ing NP–comple e P oblems wi h Ex ended Spiking
Neu al P Sys ems
In his sec ion we show ha nonde e minis ic SN P sys ems a e e y powe ul
compu ing de ices, a leas in he ex ended e sion de ined in he p e ious sec ion:
in ac , hey a e able o sol e NP–comple e p oblems in a cons an numbe o
compu a ion s eps.
3.1 Sol ing he Subse Sum p oblem
Le us i s conside he Subse Sum p oblem, which can be s a ed as ollows.
P oblem 1. Name:Subse Sum.
•Ins ance: a (mul i)se V={ 1, 2,..., n}o posi i e in ege numbe s, and
a posi i e in ege numbe S
•Ques ion: is he e a subse B⊆Vsuch ha P
b∈B
b=S?
I we allow o nonde e minis ically choose among he ules which occu in he
neu ons, hen he ex ended SN P sys em depic ed in Figu e 1 sol es any gi en
ins ance o Subse Sum in a cons an numbe o s eps. We emphasize he ac
On he Compu a ional Powe o SN P Sys ems 233
Fig. 1. A nonde e minis ic ex ended SN P sys em ha sol es he Subse Sum p oblem
in cons an ime
ha such a solu ion occu s in he semi-uni o m se ing, ha is, o e e y ins ance
o Subse Sum we build an SN P sys em ha speci ically sol es ha ins ance.
Le (V={ 1, 2,..., n}, S) be he ins ance o Subse Sum o be sol ed, and
le B⊆V. In he ini ial con igu a ion o he sys em, he le mos neu ons con ain
( om op o bo om) 1, 2,..., nspikes, espec i ely, whe eas he igh mos
neu ons con ain ze o spikes each. In he i s s ep o compu a ion, in each o he
le mos neu ons o he SN P sys em depic ed in Figu e 1 i is nonde e minis ically
chosen whe he o include o no he elemen iin B; his is accomplished by
nonde e minis ically choosing among one ule ha o ge s ispikes (in such a
case, i6∈ B) and one ule ha p opaga es ispikes o he igh mos neu ons. A
he beginning o he second s ep o compu a ion a ce ain numbe No spikes, ha
co esponds o he sum o he iwhich ha e been chosen, occu s in he igh mos
neu ons. We ha e h ee possible cases:
•N < S: in his case nei he he ule aS→a; 0 no he ule aS+1 →a; 1
(which occu in he neu on a he op and a he bo om o he second laye ,
espec i ely) i e, and hus no spike is emi ed o he en i onmen ;
•N=S: only he ule aS→a; 0 i es, and emi s a single spike o he en i on-
mnen . No u he spikes a e emi ed;
•N > S: bo h he ules aS→a; 0 and aS+1 →a; 1 i e. The i s ule im-
media ely sends one spike o he en i onmen , whe eas he second ule sends
ano he spike a he nex compu a ion s ep (due o he delay associa ed wi h
he ule).
234 A. Lepo a i e al.
Hence, by coun ing he numbe o spikes emi ed o he en i onmen a he second
and hi d compu a ion s eps we a e able o ead he solu ion o he gi en ins ance
o Subse Sum: he ins ance is posi i e i and only i a single spike is emi ed.
The o mal de ini ion o he ex ended (gene a ing) SN P sys em depic ed in
Figu e 1 is as ollows:
Π= ({a}, σ1,...,σn+2, syn, ou ),
whe e:
•σi= ( i,{a i→λ, a i→a i; 0}) o all i∈ {1,2,...,n};
•σn+1 = (0,{aS→a; 0});
•σn+2 = (0,{aS+1 →a; 1);
•syn =Sn
i=1{(i, n + 1),(i, n + 2)};
•ou = 0 indica es ha he ou pu is sen o he en i onmen .
Howe e , he e we a e aced wi h a p oblem ha we ha e al eady encoun e ed
in [10], and ha we will encoun e again in he es o he pape . In o de o clea ly
expose he p oblem, le us conside he ollowing algo i hm ha sol es Subse
Sum using he well-known Dynamic P og amming echnique [3]. In pa icula , he
algo i hm e u ns 1 on posi i e ins ances, and 0 on nega i e ins ances.
Subse Sum({ 1, 2,..., n}, S)
o j←0 o S
do M[1, j]←0
M[1,0] ←M[1, 1]←1
o i←2 o n
do o j←0 o S
do M[i, j]←M[i−1, j]
i j≥ iand M[i−1, j − i]> M[i, j]
hen M[i, j]←M[i−1, j − i]
e u n M[n, S]
In o de o look o a subse B⊆Vsuch ha Pb∈Bb=S, he algo i hm uses an
n×(S+ 1) ma ix Mwhose en ies a e om {0,1}. I ills he ma ix by ows,
s a ing om he i s ow. Each ow is illed om le o igh . The en y M[i, j]
is illed wi h 1 i and only i he e exis s a subse o { 1, 2,..., i}whose elemen s
sum up o j. The gi en ins ance o Subse Sum is hus a posi i e ins ance i and
only i M[n, S] = 1 a he end o he execu ion.
Since each en y is conside ed exac ly once o de e mine i s alue, he ime
complexi y o he algo i hm is p opo ional o n(S+1) = Θ(nS). This means ha
he di icul y o he p oblem depends on he alue o S, as well as on he magni ude
o he alues in V. In ac , le K=max{ 1, 2,..., n, S}. I Kis polynomially
bounded wi h espec o n, hen he abo e algo i hm wo ks in polynomial ime.
On he o he hand, i Kis exponen ial wi h espec o n, say K= 2n, hen he
abo e algo i hm wo ks in exponen ial ime and space. This beha io is usually
On he Compu a ional Powe o SN P Sys ems 235
e e ed o in he li e a u e by elling ha Subse Sum is a pseudo–polynomial
NP–comple e p oblem.
The ac ha in gene al he unning ime o he abo e algo i hm is no poly-
nomial can be immedia ely unde s ood by compa ing i s ime complexi y wi h he
ins ance size. The usual size o he ins ances o Subse Sum is Θ(nlog K), since
o conciseness e e y “ easonable” encoding is assumed o ep esen each elemen
o V(as well as S) using a s ing whose leng h is O(log K). He e all loga i hms a e
aken wi h base 2. S a ed di e en ly, he size o he ins ance is usually conside ed
o be he numbe o bi s which mus be used o ep esen in bina y Sand all he
in ege numbe s which occu in V. I we would ep esen such numbe s using he
una y no a ion, hen he size o he ins ance would be Θ(nK). Bu in his case we
could w i e a p og am which i s con e s he ins ance in bina y o m and hen
uses he abo e algo i hm o sol e he p oblem in polynomial ime wi h espec
o he new ins ance size. We can hus conclude ha he di icul y o a nume ical
NP–comple e p oblem depends also on he measu e o he ins ance size we adop .
The p oblem we men ioned abo e abou he SN P sys em depic ed in Figu e
1 is ha he ules a i→λand a i→a i; 0 which occu in he le mos neu ons,
as well as hose ha occu in he igh mos neu ons, check o he exis ence o a
numbe o spikes which is exponen ial wi h espec o he usually ag eed ins ance
size o Subse Sum. Mo eo e , o ini ialize he sys em he use has o place a
numbe o objec s which is also exponen ial. This is no ai , because i means
ha he SN P sys em ha sol es he NP–comple e p oblem has an exponen ial
size wi h espec o he bina y s ing which is used o desc ibe i ; an exponen ial
e o is hus needed o build he sys em, ha easily sol es he p oblem by wo king
in una y no a ion (hence in polynomial ime wi h espec o he size o he sys em,
bu no wi h espec o i s desc ip ion size). This p oblem is in some aspec s simila
o wha has been desc ibed in [10], conce ning adi ional P sys ems ha sol e
NP–comple e p oblems.
3.2 The 3-SAT p oblem
In his sec ion we show ha SN P sys ems a e also able o sol e non-nume ical
NP–comple e p oblems. Such p oblems a e inhe en ly s ongly NP–comple e, ha
is, hey emain NP–comple e e en i he numbe s e en ually con ained in o he
ins ance a e exp essed in una y o m. Speci ically, we i s p opose a simple ex-
ended SN P sys em ha sol es 3-SAT, and hen we show ha also s anda d SN
P sys ems a e able o sol e his p oblem.
We s a by ecalling some well known de ini ions, in o de o se le he no a-
ion. A boolean a iable is a a iable which can assume one o wo possible u h
alues: ue and alse. As usually done in he li e a u e, we will deno e ue
by 1 and alse by 0. A li e al is ei he a di ec ed o a nega ed boolean a iable.
Aclause is a disjunc ion o li e als, whe eas a 3-clause is a disjunc ion o exac ly
h ee li e als. Gi en a se X={x1, x2,...,xn}o boolean a iables, an assignmen
is a mapping a:X→ {0,1} ha associa es o each a iable a u h alue. The
242 A. Lepo a i e al.
Thus, a s ep o he spiking phase equi es O(mlog D)·m·(m2+ log D+ log(w+
Qm))=O(m2log D)(m2+ log D+ log(w+ Qm))s eps.
The o al ime equi ed o simula e s eps o Πis hus imes he ime needed
o pe o m he wo phases, ha is, ·O(m(Z+ log(w+ Qm) + log Q+ log D)) +
O(m2log D)(m2+ log D+ log(w+ Qm)).
To show ha his ime is polynomial wi h espec o he desc ip ion size o he
sys em Π, we need o explici he ime Z equi ed o selec which ule has o be
applied in neu on σi. We s ess he ac ha , since he sys em Πis de e minis ic,
a each compu a ion s ep he e is a mos one ule in σiwhich can i e. In o de
o selec such a ule, we need o check whe he he e a e enough spikes in he
neu on (and clea ly his can be done in polynomial ime), as well as o check i
ni∈L(Ei). In gene al, his las ope a ion canno be done in polynomial ime,
as i will be p o ed in he nex p oposi ion. None heless, in [9] i is shown ha
uni e sali y can be ob ained by using SN P sys ems whe e he egula exp essions
associa ed wi h each ule a e o e y simple o ms: ai, wi h i≤3, o a(aa)+.
Conside ing such sys ems, i is easy o see ha he ime equi ed o check i he
con en s o σiis in he egula se de ined by he egula exp ession can be done
in polynomial ime, since in he o me case i su ices o check i he numbe is
equal o i( ime p opo ional o log ni), whe eas in he la e case i su ices o
check he las bi o ni.
Thus, he ime equi ed o selec he ule o apply depends on he numbe o
ules in each neu on. Tha is, Zi=O(|Ri|) = O( ), whe e = max1≤i≤m|Ri|is
he maximum numbe o ules which can be con ained in a neu on.
As a consequence, he o al ime equi ed o simula e s eps o Πis ·O(m( +
log(w+ Qm) + log Q+ log D)) + O(m2log D)(m2+ log D+O(log(w+ Qm)).
We conclude his sec ion by s essing ha he abo e simula ion could be pe -
o med in polynomial ime because he egula exp essions used in he ules a e o
a e y es ic ed o m. Indeed, he e is a la ge amoun o compu a ional powe hid-
den in o he implici mechanism ha SN P sys ems use o decide whe he a gi en
ule can be applied o no , as p o ed in he ollowing p oposi ion. The di icul y
o checking whe he he con en s o a neu on is in o he egula se de e mined by
he egula exp ession Eo he ule is induced by he ac ha we a e dealing wi h
una y languages. As old abo e, in hese languages a s ing is uniquely de e mined
by i s leng h. Hence, a compac ep esen a ion o he s ing is ob ained by w i ing
(in bina y) i s leng h, a he han by w i ing he s ing i sel . This is an expo-
nen ially smalle ep esen a ion, and consequen ly all he p oblems de ined upon
his ep esen a ion become ha de , as i happens o all “succin ” ep esen a ions
(see [15], chap e 20). Conce ning he succin e sion o he membe ship p oblem
(is a gi en s ing in o he language gene a ed by E?) we can p o e he ollowing
p oposi ion.
P oposi ion 1. Le Πbe an SN P sys em ha ing a single neu on, ha con ains
he ule E:ac→a;d, whe e c≥1and d≥0a e na u al numbe s, and E is
any egula exp ession ( o a una y language de ined on he alphabe {a}). I E

On he Compu a ional Powe o SN P Sys ems 243
is desc ibed in a succin o m, hen deciding whe he his ule can be applied is a
leas NP–comple e.
P oo . Le us show a polynomial ime educ ion om Subse Sum o his p oblem.
Le (V={ 1, 2,..., n}, S) be an ins ance o Subse Sum. I we pu K=
max{ 1, 2,..., n, S}, hen he ins ance size is Θ(nK), as discussed in sec ion
3.1. Conside he egula exp ession E=E1◦E2◦...◦En, whe e Ei= (λ∪{a i}),
wi h λ he symbol ha ep esen s he emp y wo d. Since we a e dealing wi h una y
languages in succin o m, e e y s ing o L(E) can be uniquely de e mined by i s
leng h, and hus we can w i e L(Ei) = {0, i}.L(E) is jus ob ained by pe o ming
a language heo e ic conca ena ion among he languages L(Ei): L(E) = L(E1)◦
L(E2)◦...◦L(En). Clea ly, he egula exp ession Ecan be ep esen ed using a
s ing whose leng h is polynomial wi h espec o he size o he gi en ins ance o
Subse Sum. I is immedia ely e i ied ha L(E) con ains 2nelemen s, bijec i ely
associa ed wi h he subse s o V. Mo eo e , aS∈L(E) i and only i he e exis s
a se B⊆Vsuch ha Pb∈Bb=S. Hence, checking whe he aSis in L(E) o no
is equi alen o sol e he Subse Sum p oblem on he gi en ins ance (V, S).
5 Conclusions and Di ec ions o Fu u e Resea ch
In his pape we ha e s a ed o s udy he compu a ional powe o spiking neu al
P sys ems. In pa icula , by sligh ly ex ending he o iginal de ini ion gi en in [8]
and [9] we ha e shown ha by exploi ing nonde e minism i is possible o sol e
NP–comple e p oblems such as Subse Sum and 3-SAT.
Conce ning de e minis ic sys ems, we ha e shown ha he uni e sal de e -
minis ic SN P sys ems de ined in [8, 9] can be simula ed by de e minis ic Tu ing
machines wi h a polynomial slowdown. Su p isingly, his was possible only be-
cause he uni e sal P sys ems desc ibed in [8, 9] use egula exp essions o a e y
es ic ed o m. In ac , i was shown ha i we allow he use o gene al egula
exp essions hen we can exploi he mechanism used by SN P sys ems o decide
whe he he con en s o a neu on ma ches a egula exp ession o sol e he NP–
comple e p oblem Subse Sum.
Fu he esea ch is needed o ully unde s and he powe o accep ing SN P
sys ems. In pa icula , by encoding hei inpu s as he dis ance be ween subsequen
spikes we a e limi ing ou sel es o use numbe s exp essed in una y no a ion. A
mo e compac way o encode a k-bi na u al numbe nwould be o send a sequence
o spikes du ing a p e ixed sequence o kcompu a ion s eps: he p esence o a spike
indica es a 1, i s absence indica es a 0. I is no cu en ly known whe he in his
way SN P sys ems can s ill sol e nume ical NP–comple e p oblems such as Subse
Sum, o whe he a subsys em ha con e s in ege numbe s om bina y o una y
no a ion can be designed, as i was made in [10] o adi ional P sys ems.
244 A. Lepo a i e al.
Acknowledgmen s
We g a e ully hank Gheo ghe P˘aun o in oducing he au ho s o he s imula ing
subjec o spiking neu al P sys ems, and o asking us a “Milano heo em” (in he
spi i o [22]) abou hei compu a ional powe , du ing he Fi h B ains o ming
Week on Memb ane Compu ing, held in Se ille om Janua y 29 h o Feb ua y 2nd,
2007. Mo eo e , we a e eally indeb ed wi h him o sugges ing us he s anda d
nonde e minis ic SN P sys em ha sol es 3-SAT, exposed in sec ion 3.
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