A) Bioinformatics B) Seismic exploration C) Cryptographic use D) Gambling
A) Integrated neural clusters B) High Shannon entropy C) Random seeds external to the software D) Analog processing methods
A) By using semiotic signs B) Through Shannon entropy C) Via extractors D) Via digital noise
A) Free energy B) Dynamic core hypothesis C) Min-entropy D) Effective information
A) Rényi entropy B) Thermal entropy C) Algorithmic entropy D) Conditional entropy
A) In seismic oil exploration B) In semiotic code control C) In evaluating randomness in cryptographic systems D) In minimizing free energy
A) Only in cryptographic systems B) Yes C) No D) Only for pseudorandom numbers
A) Black hole analysis B) Bioinformatics C) Seismic oil exploration D) Search for extraterrestrial intelligence
A) Minimize free energy in the brain B) Decode dominant social messages C) Strip off and separate unwanted noise from the desired seismic signal D) Generate secure pseudorandom numbers
A) Cryptographically secure pseudorandom number generators B) Information theory and digital signal processing C) Free energy principles D) Extractors and Rényi entropy
A) Doede Nauta and Winfried Nöth B) Karl J. Friston and Andrey Kolmogorov C) Umberto Eco and Ferruccio Rossi-Landi D) Gerald Edelman and Giulio Tononi
A) The separation of unwanted noise from seismic signals B) The minimization of free energy in a self-organized system C) The study of the internal processes of coding, filtering, and information processing D) The measurement of sufficient randomness in extractors
A) Umberto Eco and Ferruccio Rossi-Landi B) C.E. Shannon and R.V.L. Hartley C) Gerald Edelman and Karl J. Friston D) Doede Nauta and Winfried Nöth
A) Through digital signal processing of seismic signals B) By utilizing cryptographically secure pseudorandom seeds C) By applying the free energy principle D) By using signs that exhibit a high degree of redundancy
A) To extract random numbers for cryptography B) To explore seismic oil deposits C) To study black holes and bioinformatics D) To analyze the integrated process organization of neural information
A) The paradox of extraterrestrial intelligence B) The binding problem in cognitive neuroscience C) The problem of algorithmic complexity D) The issue of seismic noise filtering
A) R.V.L. Hartley and C.E. Shannon B) Doede Nauta and Winfried Nöth C) Gerald Edelman and Giulio Tononi D) Umberto Eco and Ferruccio Rossi-Landi
A) Min-entropy B) Effective information C) Shannon entropy D) Seismic signal processing
A) External cryptographic random seeds B) Analog methods of data transmission C) A reentrant process organization D) A high degree of redundancy in signs
A) The coding and filtering processes studied in semiotics B) The synchronization of neurophysiological activity between groups of neuronal populations C) The filtering of unwanted noise from desired seismic signals D) The generation of pseudorandom numbers using extractors
A) Gerald Edelman B) Giulio Tononi C) Charles Sanders Peirce D) Karl J. Friston
A) A self-organized system B) A cryptographic random number generator C) A dominant social class D) An analog seismic receiver
A) The Bayesian brain hypothesis B) The semiotic information theory C) The dynamic core hypothesis D) The integrated information theory
A) Astrology B) Phrenology C) Search for extraterrestrial intelligence D) Alchemy
A) Neural clusters B) Tectonic plates C) Seismic waves D) Black holes
A) Biophysics B) Bioinformatics C) Biochemistry D) Biomechanics
A) Crosswords B) Gambling C) Cipher creation D) Chess
A) Gerald Edelman B) Umberto Eco C) R.V.L. Hartley D) Doede Nauta
A) Winfried Nöth B) Giulio Tononi C) Ferruccio Rossi-Landi D) C.E. Shannon
A) Andrey Kolmogorov B) Winfried Nöth C) Charles Sanders Peirce D) Karl J. Friston
A) History of information theory B) Dynamic core hypothesis C) Integrated information theory D) Free energy principle
A) A network B) A brute force attack C) A block cipher D) A single organ
A) Distinct physiological states B) Unicity distances C) Symmetric keys D) Information theory units
A) How it occurs B) Why brute force attacks succeed C) How encryption keys are generated D) Why it ceases permanently
A) Cryptographic interactions B) Enigma machine interactions C) One-time pad interactions D) Cardio-respiratory interactions
A) Extreme environments B) Simulated virtual environments C) Underground bunker environments D) Cryogenic laboratory environments
A) The byte B) The shannon C) The bit D) The ban
A) The Enigma project B) The Unicity project C) The Ultra project D) The Venona project
A) Symmetric key code B) Lorenz cipher code C) Enigma machine code D) One-time pad code
A) It is completely impossible under any circumstances B) It is much more difficult than it might first appear C) It is extremely easy using symmetric keys D) It requires no computational effort
A) An information-theoretic attack B) A network physiology attack C) A brute force attack D) A conditional mutual attack
A) One-time pads B) Secret key algorithms C) Unicity distance algorithms D) Asymmetric algorithms
A) Transfer entropy B) One-time pads C) Block ciphers D) Bans
A) Block ciphers B) Brute force C) Transfer entropy D) Care
A) The Network Physiology project B) The Venona project C) The Ultra project D) The Enigma project
A) Rate-distortion theory B) Channel coding C) Lossy data compression D) Lossless data compression
A) Channel resolvability B) Pragmatic information C) Rate-distortion theory D) Source-channel separation theorems
A) Bytes B) Entropy C) Bits D) Distortion functions
A) The broadcast channel B) The multiple-access channel C) The wiretap channel D) The relay channel
A) The multiple-access channel B) The broadcast channel C) The relay channel D) The wiretap channel
A) The broadcast channel B) The multiple-access channel C) The relay channel D) The wiretap channel
A) Conditional entropy B) Cross-entropy C) Kullback-Leibler divergence D) Mutual information
A) Euclidean space B) Vector space C) Metric space D) Product space
A) log2(pi) B) 1 / pi C) -ln(pi) D) -log2(pi)
A) The weighted average B) The maximum value C) The median D) The geometric mean
A) 2000 bits B) No information C) 1 shannon D) 1000 shannons
A) 1939 B) 1960 C) 1948 D) 1952
A) 1940s B) 1920s C) 1930s D) 1950s
A) Molecular biology B) Telecommunication C) Artificial intelligence D) Quantum computing
A) 0.5 bits B) 2 bits C) Zero D) 1 bit
A) DSL B) Compact discs C) ZIP files D) Voyager missions
A) DSL B) Mobile phones C) ZIP files D) Artificial intelligence
A) Apollo missions B) Voyager missions C) Curiosity rover D) Hubble telescope
A) Television B) Radio C) Steam engine D) Compact disc
A) Electric guitars B) Airplanes C) Automobiles D) Mobile phones
A) The postal service B) The printing press C) The Internet D) The telegraph network
A) Quantum computing B) Cloud computing C) Optical computing D) Distributed computing
A) Art creation B) Architectural drafting C) Sculpture casting D) Oil painting restoration
A) Acoustic room resonance B) Musical instrument design C) Vocal cord anatomy D) Music
A) Metaphysics B) Epistemology C) Aesthetics D) Ethics
A) Vannevar Bush B) Ralph Hartley C) James Gleick D) Harry Nyquist
A) 1940 B) 1948 C) 1939 D) 1928
A) Alan Turing B) James Gleick C) Vannevar Bush D) Ludwig Boltzmann
A) Harry Nyquist B) Claude Shannon C) Ralph Hartley D) Alan Turing
A) PV = nRT B) W = K log m C) E = mc2 D) H = log Sn
A) The bit B) The baud C) The byte D) The decimal digit
A) Ralph Hartley B) Harry Nyquist C) Alan Turing D) Claude Shannon
A) Rolf Landauer B) Harry Nyquist C) James Gleick D) Vannevar Bush
A) Natural logarithm B) Common logarithm C) Decimal logarithm D) Binary logarithm
A) Binary logarithm B) Base-two logarithm C) Common logarithm D) Natural logarithm
A) Binary logarithm B) Natural logarithm C) Common logarithm D) Base-e logarithm
A) A deterministic sequence B) The lowest possible information content C) The most unpredictable state D) The most predictable state
A) Base-e B) Base-256 C) Base-10 D) Base-2
A) A logarithmic trial B) A Markov trial C) An equiprobable trial D) A Bernoulli trial
A) Equivocation B) Joint entropy C) Mutual information D) Marginal entropy
A) Log-likelihood ratio B) Pointwise mutual information C) Kullback-Leibler divergence D) Transinformation
A) Thermodynamics B) Quantum mechanics C) Communication D) Macroeconomics
A) Euclidean distance B) Mahalanobis distance C) Kullback-Leibler divergence D) Jensen-Shannon divergence
A) Shapiro-Wilk test B) Log-likelihood ratio test C) Mann-Whitney U test D) Student's t-test
A) Inner product B) Semi-quasimetric C) Linear transformation D) Euclidean metric
A) Alice B) Neither C) Both D) Bob
A) Alice B) It is impossible to determine C) Both will be equally surprised D) Bob
A) An infinite continuous set B) An empty set C) A finite geometric set D) A discrete set
A) Only in macroscopic mechanics B) Only in quantum states C) Yes D) No
A) {X0, X1, ..., X_{n-1}} B) {Y1, Y2, ..., Y_n} C) {X1, X2, ..., X_n} D) {X1, Y1, ..., X_n, Y_n}
A) A result of zero B) Completely different results C) The same result D) An undefined value
A) An unpredictable random variable that changes constantly B) An inherent fixed property C) A completely controllable variable D) A negligible factor in modern systems
A) p B) i C) e D) Hb
A) Flips the input bit B) Erases the input bit C) Delays the input bit D) Duplicates the input bit
A) Ternary input B) Zero capacity C) Gaussian noise D) Memory |