McCulloch Pits algorithm with solved example

#mcculloch #neuralNetworks #softComputing
MP Neurones neural networks,soft computing
Introduction:1.1 Biological neurons, McCulloch and Pitts models of neuron, Types
of activation function, Network architectures, Knowledge representation, Hebb net
1.2 Learning processes: Supervised learning, Unsupervised learning and
Reinforcement learning
1.3 Learning Rules : Hebbian Learning Rule, Perceptron Learning Rule, Delta
Learning Rule, Widrow-Hoff Learning Rule, Correlation Learning Rule, WinnerTake-All Learning Rule
1.4 Applications and scope of Neural Networks
10
2
Supervised Learning Networks :
2.1 Perception Networks - continuous & discrete, Perceptron convergence theorem,
Adaline, Madaline, Method of steepest descent, - least mean square algorithm,
Linear & non-linear separable classes & Pattern classes,
2.2 Back Propagation Network,
2.3 Radial Basis Function Network.
12
3
Unsupervised learning network:
3.1 Fixed weights competitive nets,
3.2 Kohonen Self-organizing Feature Maps, Learning Vector Quantization,
3.3 Adaptive Resonance Theory - 1
06
4
Associative memory networks:
4.1 Introduction, Training algorithms for Pattern Association,
4.2 Auto-associative Memory Network, Hetero-associative Memory Network,
Bidirectional Associative Memory,
4.3 Discrete Hopfield Networks.
08
5
Fuzzy Logic:
5.1 Fuzzy Sets, Fuzzy Relations and Tolerance and Equivalence
5.2 Fuzzification and Defuzzification
5.3 Fuzzy Controllers

[@rishabhtiwari3463]

Who's here one night before the exam👍👍😭😭

[@jettiteja5805]

An hour before exam ._.

[@AbhishekSingh-kb5cx]

15 days before exam

[@nikhilrocky5518]

Day before exam preparing for semester😥😥😥

[@bhanuprasaddasari7960]

Just 9 hrs before the exam but feeling sleepy so just commenting sleeping 😴

[@javiercristiano6690]

Instablaster.

[@yasssh7835]

Dude just explained the shit which my 60yr univ teacher can't in her entire career.

[@yashgupta1633]

Real

[@sumeshkumar9940]

RIP at 3:43

[@anshulsharma5920]

Bhai itni jaldi kyo he Kahi Jana he kya 😂😂

[@samadrien6563]

Nee pwoli aanu mwuthe

[@strolla2501]

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Pray constantly and read the Bible continuously.
(Acts 3:13--20)
Reach out to GOD daily to guide you into perfect righteousness. Love your enemies and genuinely pray for their righteousness (Matthew 5 vs 48).
Read the Bible and obey JESUS CHRIST always and in all things. THANKS TO JESUS CHRIST. AMEN.

[@arindamroy7671]

The fuck ?

[@strolla2501]

Can you do an example, just showing how to find the threshold outside of any logic gate. That is,inputs are given, weights for each input is given and then we want to find the output. (No logic gate involved)

[@zohaibramzan6381]

U used wrong value of weights.For inhibitory inputs weight must be 1 and for excitatory it should be 0.

[@snigdharoy1938]

Very Nice Explanation 👍

[@AdiKSingh19xx]

You have written the truth table of XOR.

[@vidushiagrawal3355]

Please try to teach in hindi more..m not saying because of language issue but while trying to teach in English u r just reading what is already written there!

[@lifethrownoutofthewindow]

nw+p hai bhai

[@WESMITH91]

Mike McCullough - are you involved in this? Do you agree??

[@kingage4138]

1 day 😂

[@ShivamSharma-rx3bd]

who is watching this video in lockdown.

[@john_slickk2204]

Thnk u so much, clear cut explaination with great examples!!

[@YashKakrecha]

What is k? Can you explain? In my book there is k. kw > theta > (k-1)w , like this?

[@عبدالرحمنفؤاد-و1ث]

why do you explain quickly.. are you basy!

[@dweepchande2366]

Wrong Truth table and rushing the explanation .

[@lizzmk]

Gud one and one more request can u make another video for XOR too?

[@usaama.1]

Who’s here one night before exam 🤣🤣

[@ankitfernandez370]

Watching it during the exam 😂😂

[@arpitkesarwani6123]

Nice video

[@anishkadve7214]

7 minutes before exam🥀💀

[@tanujaSangwan]

good handwriting

[@prachichandrakar2367]

Very fast voice telling need high concentration to understand

[@partharanke5925]

You need a brain too.

[@arindamroy7671]

@@partharanke5925 Good one xD LOL

[@chaitanyagupta6668]

easily solved by slowing down the playback speed.

[@parashar6307]

Normal video bhi aisa lg rha h jaise 2x me chal rha ho

[@rahulprasad7865]

But how and not logic was performed 1,0 =1??

[@btechtutorialByNishantMittal]

ANDNOT Gate calculates the function A and not B.Therefore it has a value of 1 when A is 1 and B is 0 and 0 for all other cases.

[@rahulprasad7865]

@@btechtutorialByNishantMittal means output is A Bbar

[@saikirangaddam3670]

Fake

[@vedkhetle5849]

beautifully explained

[@bheemaram2177]

Just in online exam 🤣🤣

[@EIC1722]

I NEED
USING McCulloch pit model nor and nand xor gate function urgent

[@Phoenix-wr6rn]

Need more problems please

[@anupamguptaroy7106]

Bhai sirf notes mese read hi karna hota toh mai khud hi padh leta

[@aashishaxis5108]

Do we use weights in McCullouch and Pitts neural network?

[@yogeshsariya4259]

I guess ....NO we do not

[@saurabhmiskin6254]

thank you so much.... u r so good at explanation...

[@manasmungi634]

1 hrs before exam 😅

[@rohitgehlot]

Nand gate ki truth table galat banayi hee aapne

[@souravbhagat1358]

Plz make a vedio using And OR function using MCp modle

[@aish_waryaaa]

Thank You So Much really explained in a systematic way...GOD BLESS YOU.

[@strolla2501]

Good job. Thank you.

[@dipanmukhopadhyay2804]

Man you are doing well like really well explained

[@sanidhyachaudhary8657]

Fraud

[@demetriusdemarcusbartholom8063]

ECE 449

[@chetanraj1950]

For the first case, If you set the value for theta >=2, then neuron will fire. Then why will we go for the second case by taking w1=1 and w2=-1?

[@gautamsardana4368]

Chetan Raj you need the neuron to be fired only for the case 1,0

[@chetanraj1950]

@@gautamsardana4368 I know, But if we take the theta>=2,. Then also it will fire right?

[@gautamsardana4368]

@@chetanraj1950 it will fire, sure. But, it will fire only for 1,1. You want it to fire for 1,0 only since andnot of 1,0 is 1 and 0 for rest.

[@chetanraj1950]

@@gautamsardana4368 Yes, I understood. Thank You.

[@mgaurs]

I am watching this..and my exam is after 1 hour 😁

[@rohitkadu4089]

nicely explain..keep it up

[@bhavya2301]

Good Explanation.But Could Have Been Better.

[@jerryjohn1995]

Everything is perfect expect that pencil, please sharpen it

[@sabamanzoor5639]

Good job!If you could have also provided a pdf file of this notebook ,that would ve been great

[@jrseinc]

thank you soo much!

[@denj4s]

I love this accent, but the explanation is even better

[@mertozdemir9489]

helal olsun aslan parçası

[@dhanashriasade4741]

Thank you so much for clear explanation 👍

[@Weekend_vloger_yt]

thanks for helping

[@aryalk850]

I don't understand how the first case can't fire neuron

[@krishnakrmahto97]

in the first case, you cannot find a suitable threshold for which the o/p neuron fires only for input (1,0) (this is what we want the neuron to do to simulate AND-NOT logic). Any threshold you choose will make the neuron fire for all the possible inputs (this does not simulate AND-NOT logic).

[@EntropyOnTheCrosshair]

How is theta >= 1 wrong since it fires only those cases where it's supposed to fire?

[@EntropyOnTheCrosshair]

@@krishnakrmahto97 I don't understand.

[@krishnakrmahto97]

@@EntropyOnTheCrosshair in the first case , it will fire for cases other than what is desired for theta≥1..in the second case it's fine.

[@sushilkumarm4088]

Please reduce the speed.

[@premgupta6417]

Hey! You can use the Playback speed option in settings and set it to 0.75...

[@sumeshkumar9940]

what a noob😂

[@kushgupta1673]

thank you so much

[@prayagasrikar8250]

thanks bro

[@strolla2501]

At 4:40 , you said that we would not consider the sign. I thought that we where counting the number of negative weights, that is, 1. Or are we supposed to sum the magnitudes of the negatives weights?

[@bhaveshchaudhary4571]

To the point man ,nice explanation 😉

[@abhinavrautela6493]

Please suggest weights for AND implementation

[@btechtutorialByNishantMittal]

You can assume both weights to be excitatory.

[@abhinavrautela6493]

@@btechtutorialByNishantMittal but it won't provide solution as both excitatory will produce three Y in greater than 0 and won't give solution

[@btechtutorialByNishantMittal]

Only the value of yin corresponding to the case when both inputs are 1 will be greater than 0.For other cases it will be 0,0 and -2(assuming you are taking input values to be bipolar)

[@sanskritikesarwani475]

Sir low your speed a little

[@simransingh6137]

Thank you sir

[@buhimanshu]

Nice and satisfied, but model for logic, you drawn in last should have more informable.

[@rahuljadav1097]

Thank you 😊

[@kalyanichowdary6294]

Still I have some doughts in this concept could you please solve

[@tanaysalve2702]

Hello Thank you for the better understanding but I had a query that I request you to resolve . For the implementation of NOR gate using McCulloch-Pitts Model can we have a different approach such as instead of replacing w11 and w12 can we perform this approach in order to gain the same proof such as Row 1: w11 = 1 ; w12 = 1 ; deta1 = 1
Row 2: w11 = 1 ; w12 = 1 ; deta1 = -0.5
Row 3: w11 = 1 ; w12 = 1 ; deta1 = -0.5
Row 4: w11 = 1 ; w12 = 1 ; deta1 = -2.5. Please!

[@shaikmehnaaztabasum7460]

thank you soo much very nice explanation :)

[@doctoronline461]

excellent way of teaching ...............wonderful

[@animeshbanerjee4379]

Here in 4:41 how the value of theta become 1 ? Bcz theta = (2*1*(-1)) = 2 ?

[@priyadharshans4745]

you are considering only the magnitude of w and p....
i.e. w= |w| =|1| = 1
p=|p| =|-1| = 1
now nw-p = 2(1)-1 = 1

[@DeepakGupta-gu3ul]

👍👍👍

[@bindhujajemi3205]

Can the threshold be negative and decimal for cases like NOT ?

[@yeshwanthreddy9242]

I understood the concept. But how are you deciding the weights? Which input gets excitatory and which one gets inhibitory weights? You just to 2 assumptions 1st (w1=1, w2=1) and the 2nd (w1=1,w2=-1) which worked. As Machine learning doesn't work on assumptions and it would take forever for it if there were 1000s of weights, I would like to know which algorithm will decide these weights and how. Please do make a video on that.

[@noelthomasbejoy3089]

Yeshwanth Reddy you have to try different combo of (1,-1),no fixed way

[@yeshwanthreddy9242]

@@noelthomasbejoy3089 that will be (no of weights)^2 which will increase exponentially as no of weights increases. It's impossible compute such a large no of weights. There must be some other smart way to achieve this....🤔.

[@amoghkulkarni3519]

very well explained , keep up the good work

[@rahulprasad7865]

Thanks man

[@buhimanshu]

Suggest weights for NOR gate.

[@bhushan8755]

Thanks bro. keep it up

[@bekaddourfatima4633]

how do you choose the weights for others examples. Are there any procedure??

[@btechtutorialByNishantMittal]

You will have to assume weights and see if it fires neuron for a particular case.There is no fixed procedure.

[@bekaddourfatima4633]

Thank you

[@abhishekbajpai4343]

Please explain it properly before solving question...

[@srinathsesaya7432]

Thank you

[@rahulprasad7865]

Keep going

[@REPATHATHYALA]

Do we have "w" in MP Neuron...???

[@btechtutorialByNishantMittal]

Sorry,I didn’t get your question.

[@gurjotsingh6898]

Weight from Xi node to Y

[@gssnhimabindu8831]

some people consider weights and some people don't

[@thekkedan]

how can find value of p ?

[@aadityanaik1655]

assume it

[@adityamishra7711]

PLEASE PLEASE PLEASE ANSWER ITS REALLY IMPORTANT -
Can the threshold take negative values in mcculoch pitts neuron model ?