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