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