quiz bu lëkkale ak tegtal · Dëgër Niveau

Echo State Reseau ak Reservoir

Saytu dinaamiku reservoir bu takku, liñu tàggat, mémoire buy jeex, rayon spectral ak xayma yi ci ginaaw xam-xam reservoir yi.

Yooni njiit yu jëm ciEcho State Reseau ak ordinatëru reservoir
Laaj 1 de 8

Ci Reseau Echo State, ban poid lañuy tàggat?

Xoolaatal laaj bu nekk8 laaj

Sooy def quiz bi, tontu yi ak leeral yi dañuy feeñ.

  1. Ci Reseau Echo State, ban poid lañuy tàggat?
    • poid yiy génne (lire) kese
    • Bépp diisaay buy dellusi ci biir reservoir bi
    • poids yiñ dugal kese
    • Amul benn poid buñu musa tàggat
  2. Which condition expresses the echo state property for two runs with the same input history?
    • Their recurrent weights must all be trained by backpropagation
    • Their reservoir states eventually become independent of different initial states
    • Their output weights must have spectral radius exactly one
    • Their hidden states must equal the raw input at every step
  3. Lan moo waral tàggat ESN di gëna gaaw tàggat LSTM buñ miin?
    • ESNs duñu jëfandikoo benn neuron
    • ESN yi duñu dox ludul ci ordinatër kwantum
    • ESNs moytu backpropagation-ci-jamono ci saafara liñ ligneer rek
    • ESN yi soxla wuñu ay done yuñ dugal
  4. How is spectral radius commonly used when tuning an echo-state reservoir?
    • It directly sets the number of readout classes
    • It guarantees fading memory for every recurrent matrix
    • It measures the number of trainable reservoir weights
    • It is a recurrent-feedback scale heuristic for balancing rich dynamics and stability, not a complete guarantee of the echo state property
  5. Kan moo dugal masin yiy wax ci réew mi, di xeetu ordinatëru reservoir bu am neuron yuy gëna yokk?
    • Wolfgang maass
    • Jeofrey Hinton
    • André Ng
    • Yosua Bengiyo
  6. What does the fixed reservoir compute before the ESN readout produces an output?
    • A normalized probability over all possible weights
    • A high-dimensional dynamic state representation of recent inputs
    • A learned transition table for every future sequence
    • A separate trained policy for each output class
  7. What method is commonly used to fit an Echo State Network’s readout weights?
    • Backpropagation through all fixed recurrent weights
    • Dynamic routing by agreement
    • Linear least-squares regression, often with ridge regularization
    • A softmax over reservoir eigenvalues
  8. What does the spectral radius of a recurrent weight matrix mean?
    • The sum of all matrix entries
    • The number of nonzero output weights
    • The average magnitude of the input sequence
    • The largest absolute value among its eigenvalues