Igualdad de dos bits: (A1 XNOR B1) AND (A0 XNOR B0)
Igualdad de dos bits, XNOR(A1, B1) AND XNOR(A0, B0): los dos pares de bits deben coincidir. Dieciséis filas con cuatro verdaderas, una FNC de ocho literales frente a una FND de dieciséis, y un mapa en el que ningún par de unos se toca.
Dos números de dos bits son iguales cuando sus bits altos coinciden y sus bits bajos coinciden. XNOR es la prueba de igualdad de un bit, así que la fórmula une dos de ellas con AND. La lectura del motor dice que equal se cumple exactamente cuando A1 y B1 tienen el mismo valor y A0 y B0 tienen el mismo valor. Con cuatro entradas la tabla tiene dieciséis filas, y la salida es verdadera en cuatro, Σm(0, 3, 12, 15): 00 = 00, 01 = 01, 10 = 10 y 11 = 11.
La tautología se viola con el contraejemplo A1 = FALSO, B1 = FALSO, A0 = FALSO, B0 = VERDADERO; la satisfacibilidad se cumple con las cuatro entradas en FALSO. El simplificador no encontró ninguna ley aplicable a los tres operadores. Las formas normales difieren en tamaño: la FNC, con dos eliminaciones de XNOR, es (A1 OR NOT B1) AND (NOT A1 OR B1) AND (A0 OR NOT B0) AND (NOT A0 OR B0), ocho literales; la FND necesita además una distributividad y tiene cuatro términos de cuatro literales, dieciséis. El mapa de Karnaugh dibuja cuatro grupos de una celda, cuatro implicantes primos. Compuertas: 47 NAND, 23 NOR.
Los comparadores de igualdad están en la unidad de saltos de todo procesador y en la comparación de etiquetas de toda caché, y la estructura crece añadiendo un XNOR por bit bajo el AND. En software lo mismo es un método de igualdad campo a campo. Lo que hay que vigilar es la asimetría de tamaño: la forma de producto de sumas se mantiene pequeña porque la igualdad es una conjunción de pruebas pequeñas, mientras que la forma de suma de productos tiene que enumerar cada par de valores coincidentes. Elige la forma que encaje con la estructura de la pregunta.
equal := XNOR(A1, B1) AND XNOR(A0, B0) · salida
Comprobaciones exactas
Tabla de verdad (16 filas)
| # | A1 | B1 | A0 | B0 | equal |
|---|---|---|---|---|---|
| 0 | FALSO | FALSO | FALSO | FALSO | VERDADERO |
| 1 | FALSO | FALSO | FALSO | VERDADERO | FALSO |
| 2 | FALSO | FALSO | VERDADERO | FALSO | FALSO |
| 3 | FALSO | FALSO | VERDADERO | VERDADERO | VERDADERO |
| 4 | FALSO | VERDADERO | FALSO | FALSO | FALSO |
| 5 | FALSO | VERDADERO | FALSO | VERDADERO | FALSO |
| 6 | FALSO | VERDADERO | VERDADERO | FALSO | FALSO |
| 7 | FALSO | VERDADERO | VERDADERO | VERDADERO | FALSO |
| 8 | VERDADERO | FALSO | FALSO | FALSO | FALSO |
| 9 | VERDADERO | FALSO | FALSO | VERDADERO | FALSO |
| 10 | VERDADERO | FALSO | VERDADERO | FALSO | FALSO |
| 11 | VERDADERO | FALSO | VERDADERO | VERDADERO | FALSO |
| 12 | VERDADERO | VERDADERO | FALSO | FALSO | VERDADERO |
| 13 | VERDADERO | VERDADERO | FALSO | VERDADERO | FALSO |
| 14 | VERDADERO | VERDADERO | VERDADERO | FALSO | FALSO |
| 15 | VERDADERO | VERDADERO | VERDADERO | VERDADERO | VERDADERO |
Lectura en lenguaje claro
Principianteequal es verdadero exactamente cuando se cumplen las dos condiciones siguientes:
1. A1 y B1 tienen el mismo valor (ambos verdaderos o ambos falsos)
2. A0 y B0 tienen el mismo valor (ambos verdaderos o ambos falsos)
En todos los demás casos, equal es falso.
Sobre los operadores:
- AND (Y) solo es verdadero cuando todas sus partes son verdaderas.
- XNOR es verdadero cuando ambas partes tienen el mismo valor.
Intermedioequal es verdadero exactamente cuando se cumplen las dos condiciones siguientes:
1. A1 y B1 tienen el mismo valor (ambos verdaderos o ambos falsos)
2. A0 y B0 tienen el mismo valor (ambos verdaderos o ambos falsos)
En todos los demás casos, equal es falso.
Avanzadoequal es verdadero exactamente cuando se cumplen las dos condiciones siguientes [conjunción ∧]:
1. A1 y B1 tienen el mismo valor (ambos verdaderos o ambos falsos) [puerta de equivalencia (XNOR)]
2. A0 y B0 tienen el mismo valor (ambos verdaderos o ambos falsos) [puerta de equivalencia (XNOR)]
En todos los demás casos, equal es falso.
Notación formal: XNOR(A1, B1) ∧ XNOR(A0, B0)
Diagrama lógico
Simplificación paso a paso
El motor no encontró ninguna ley que acorte esta expresión; ya es tan corta como sus leyes de reescritura permiten.
XNOR(A1, B1) AND XNOR(A0, B0)
Mapa de Karnaugh
- celdas m0
NOT A1 AND NOT B1 AND NOT A0 AND NOT B0 - celdas m3
NOT A1 AND NOT B1 AND A0 AND B0 - celdas m12
A1 AND B1 AND NOT A0 AND NOT B0 - celdas m15
A1 AND B1 AND A0 AND B0
Mintérminos y maxtérminos
equal(A1, B1, A0, B0) = Σm(0, 3, 12, 15)equal(A1, B1, A0, B0) = ΠM(1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14)Orden de variables: A1, B1, A0, B0 · 16 filas
Formas normales
Forma normal conjuntiva (FNC)
(A1 OR NOT B1) AND (NOT A1 OR B1) AND (A0 OR NOT B0) AND (NOT A0 OR B0)4 cláusulas, 8 literales · complete · Eliminación de XNOR ×2
Forma normal disyuntiva (FND)
(A1 AND B1 AND A0 AND B0) OR (A1 AND B1 AND NOT A0 AND NOT B0) OR (NOT A1 AND NOT B1 AND A0 AND B0) OR (NOT A1 AND NOT B1 AND NOT A0 AND NOT B0)4 términos, 16 literales · complete · Eliminación de XNOR ×2, Distributividad ×1
Solo NAND, solo NOR
Forma solo con NAND
NAND(NAND(NAND(NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1)), NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1))), NAND(NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)), NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)))), NAND(NAND(NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1)), NAND(NAND(A1, NAND(B1, B1)), NAND(NAND(A1, A1), B1))), NAND(NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)), NAND(NAND(A0, NAND(B0, B0)), NAND(NAND(A0, A0), B0)))))47 compuertas · equivalencia verificada en todas las filas
Forma solo con NOR
NOR(NOR(NOR(NOR(NOR(A1, A1), B1), NOR(A1, NOR(B1, B1))), NOR(NOR(NOR(A1, A1), B1), NOR(A1, NOR(B1, B1)))), NOR(NOR(NOR(NOR(A0, A0), B0), NOR(A0, NOR(B0, B0))), NOR(NOR(NOR(A0, A0), B0), NOR(A0, NOR(B0, B0)))))23 compuertas · equivalencia verificada en todas las filas
La misma regla como código
Python
# -*- coding: utf-8 -*-
# Generated by Tangibool (tangibool.python/1). Do not edit by hand; regenerate from the source revision.
# Model: not stated
# Source revision: reference
# Interpretation status: not stated
"""Tangibool evaluator (decision model).
Generated deterministically from the validated Boolean model; it evaluates exactly that
model. It does not establish that the model is a complete, legal, or safe statement of a
real-world rule, and evaluating examples does not verify the rule.
Source revision: reference
Interpretation status: not stated
Exporter: 1.0.0 (format tangibool.python/1; engine 1.0.0; semantics tangibool-semantics/1)
Logic digest: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c
Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78
Inputs (dict keys, declared order) and generated parameter names:
'A1' -> input_A1
'B1' -> input_B1
'A0' -> input_A0
'B0' -> input_B0
Outputs (declared order) and their functions:
'equal' -> output_equal(inputs)
Assumptions (the declared scope, checked by in_scope(inputs)):
none; every complete assignment is in scope.
Input contract:
Every required input must be exactly True or False (type(value) is bool). Missing
inputs, None, strings, integers (including 0 and 1), and keys that are not declared
inputs raise InputError before anything is evaluated, including inputs that a
short-circuiting operator would never read. Results are always bool.
Scope:
Decision functions raise OutOfScopeError when the inputs violate an assumption; an
out-of-scope assignment is never turned into a False result. Pass check_scope=False
to evaluate without the scope check, and use in_scope(inputs) to test it separately.
Usage:
import tangibool_model as model
model.evaluate({'A1': False, 'B1': False, 'A0': False, 'B0': False})
# -> {'equal': True}
model.output_equal({'A1': False, 'B1': False, 'A0': False, 'B0': False})
# -> True
model.evaluate({'A1': 1, 'B1': False, 'A0': False, 'B0': False})
# raises InputError: 1 is an int, not a bool
"""
import collections.abc as _abc
from typing import Dict, Mapping, Tuple
__all__ = [
"MODEL_INFO",
"IDENTIFIER_MAP",
"INPUT_NAMES",
"OUTPUT_NAMES",
"ASSUMPTIONS",
"InputError",
"OutOfScopeError",
"minterm_index",
"in_scope",
"evaluate",
"output_equal",
]
MODEL_INFO = {
"format": "tangibool.python/1",
"mode": "decision",
"model": None,
"revision": "reference",
"interpretation": None,
"exporter": "1.0.0",
"engine_version": "1.0.0",
"semantics_version": "tangibool-semantics/1",
"logic_digest": "80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c",
"assumptions_digest": "d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78",
"primary_output": "equal",
"unused_inputs": (),
"subcircuits": (),
}
# Stable ID -> generated identifier (reversible mapping; names are exact, escaped strings).
IDENTIFIER_MAP = {
"v_b85aa55232f9": {"kind": "input", "name": "A1", "identifier": "input_A1"},
"v_642166f389e0": {"kind": "input", "name": "B1", "identifier": "input_B1"},
"v_022e27020ecc": {"kind": "input", "name": "A0", "identifier": "input_A0"},
"v_83a0c82dd0b4": {"kind": "input", "name": "B0", "identifier": "input_B0"},
"f_e0aba2c1efc2": {"kind": "output", "name": "equal", "identifier": "output_equal"},
}
INPUT_NAMES = ("A1", "B1", "A0", "B0")
OUTPUT_NAMES = ("equal",)
ASSUMPTIONS = ()
_DECLARED_INPUTS = frozenset(INPUT_NAMES)
_SCOPE_INPUTS = ()
_ASSUMPTION_FORMULAS = {entry["name"]: entry["formula"] for entry in ASSUMPTIONS}
class InputError(ValueError):
"""Raised when inputs are missing, undeclared, or not exactly True/False.
Every required input must satisfy type(value) is bool. Missing inputs, None, strings,
integers (including 0 and 1), and keys that are not declared inputs are rejected before
anything is evaluated. A missing input is never treated as False. The individual problems
are listed in the problems attribute.
"""
def __init__(self, problems):
self.problems = tuple(problems)
super().__init__("Invalid inputs: " + "; ".join(self.problems))
class OutOfScopeError(ValueError):
"""Raised when the inputs violate the model's assumptions (its declared scope).
Outside its assumptions the rule has no decision: this error is never a False result.
The names of the violated assumptions are in the violated attribute.
"""
def __init__(self, violated):
self.violated = tuple(violated)
details = ", ".join(name + " (" + _ASSUMPTION_FORMULAS.get(name, "?") + ")" for name in self.violated)
super().__init__(
"Out of scope: the inputs violate "
+ ("assumption " if len(self.violated) == 1 else "assumptions ")
+ details
+ ". The rule has no decision outside its assumptions; this is not a False result."
)
def _short_repr(value: object) -> str:
text = repr(value)
return text if len(text) <= 60 else text[:57] + "..."
def _checked_inputs(inputs: Mapping[str, bool], required: Tuple[str, ...], check_scope: bool) -> Dict[str, bool]:
"""Validate inputs strictly before anything is evaluated and return a plain copy."""
if type(check_scope) is not bool:
raise TypeError("check_scope must be True or False")
if not isinstance(inputs, _abc.Mapping):
raise InputError(["inputs must be a mapping from input names to True/False, got " + type(inputs).__name__])
problems = []
for key in inputs:
if type(key) is not str or key not in _DECLARED_INPUTS:
declared = ", ".join(repr(name) for name in INPUT_NAMES) or "none"
problems.append("undeclared input " + _short_repr(key) + " (declared inputs: " + declared + ")")
needed = tuple(required) + (_SCOPE_INPUTS if check_scope else ())
for name in needed:
if name not in inputs:
problems.append("missing required input " + repr(name))
for key, value in inputs.items():
if type(key) is str and key in _DECLARED_INPUTS and type(value) is not bool:
problems.append(
"input " + repr(key) + " must be True or False (type bool), got "
+ type(value).__name__ + " " + _short_repr(value)
)
if problems:
raise InputError(list(dict.fromkeys(problems)))
return dict(inputs.items())
def _require_bool_args(function: str, pairs: Tuple[Tuple[str, object], ...]) -> None:
problems = [
"argument " + repr(name) + " of " + function + " must be True or False (type bool), got "
+ type(value).__name__ + " " + _short_repr(value)
for name, value in pairs
if type(value) is not bool
]
if problems:
raise InputError(problems)
def minterm_index(*values: bool) -> int:
"""Row index of an assignment over a declared variable order.
The first value is the most significant bit, so all-False is row 0. Used for indexed
minterm (sum) and maxterm (product) forms.
"""
index = 0
for value in values:
if type(value) is not bool:
raise InputError(["minterm_index() takes True/False values, got " + type(value).__name__ + " " + _short_repr(value)])
index = index * 2 + (1 if value else 0)
return index
def _scope_values(values: Dict[str, bool]) -> Tuple[Tuple[str, bool], ...]:
"""Value of every enabled, confirmed assumption for validated inputs, in declared order."""
return ()
def _require_in_scope(values: Dict[str, bool]) -> None:
violated = tuple(name for name, holds in _scope_values(values) if not holds)
if violated:
raise OutOfScopeError(violated)
def in_scope(inputs: Mapping[str, bool]) -> bool:
"""True when the inputs satisfy every assumption (the model's declared scope).
Requires the inputs the assumptions read; raises InputError for invalid inputs.
"""
values = _checked_inputs(inputs, (), True)
return all(holds for _, holds in _scope_values(values))
# ---- Formula bodies (inputs are validated by the public functions below) ----
def _compute_output_equal(input_A1: bool, input_B1: bool, input_A0: bool, input_B0: bool) -> bool:
"""Decision output 'equal': XNOR(A1, B1) AND XNOR(A0, B0)"""
return (input_A1 == input_B1) and (input_A0 == input_B0)
# ---- Public API ----
def output_equal(inputs: Mapping[str, bool], *, check_scope: bool = True) -> bool:
"""Decision output 'equal' (stable ID f_e0aba2c1efc2).
'equal' := XNOR(A1, B1) AND XNOR(A0, B0)
Required inputs: 'A1', 'B1', 'A0', 'B0'.
Raises InputError for missing, undeclared, or non-bool inputs, and OutOfScopeError
when check_scope is True and the inputs violate an assumption.
"""
values = _checked_inputs(inputs, ("A1", "B1", "A0", "B0"), check_scope)
if check_scope:
_require_in_scope(values)
output_equal_value = _compute_output_equal(values["A1"], values["B1"], values["A0"], values["B0"])
return output_equal_value
def evaluate(inputs: Mapping[str, bool], *, check_scope: bool = True) -> Dict[str, bool]:
"""Evaluate every output (declared order); each output is computed once.
Required inputs: 'A1', 'B1', 'A0', 'B0'.
Raises InputError for missing, undeclared, or non-bool inputs, and OutOfScopeError
when check_scope is True and the inputs violate an assumption.
"""
values = _checked_inputs(inputs, ("A1", "B1", "A0", "B0"), check_scope)
if check_scope:
_require_in_scope(values)
output_equal_value = _compute_output_equal(values["A1"], values["B1"], values["A0"], values["B0"])
return {
"equal": output_equal_value,
}
PostgreSQL
-- Tangibool PostgreSQL export (tangibool.postgresql/1)
-- Target: PostgreSQL 16 or later with typed boolean inputs; tested with PostgreSQL 18.3 (PGlite 0.5.8).
-- Not a claim of compatibility with other SQL dialects.
-- Model: not stated
-- Source revision: reference
-- Interpretation status: not stated
-- Exporter: 1.0.0 (engine 1.0.0; semantics tangibool-semantics/1)
-- Logic digest: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c
-- Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78
-- Mode: decision
--
-- Read-only: this file contains only WITH / VALUES / SELECT statements. No DDL, DML,
-- procedures, credentials, network access, or database changes. The expressions are pure
-- Boolean expressions, so their result does not depend on SQL evaluation order.
--
-- NON-NULL INPUT PRECONDITION: NULL is not a truth value of this rule. Every fragment below
-- is defined only when every input column it reads is a non-NULL boolean. The guard template
-- (section 2) marks any NULL input as 'invalid_input' and any row that violates the
-- assumptions as 'out_of_scope', and fills output columns only for 'ok' rows; a NULL in an
-- output column of another row is an envelope marker, not a third truth value. Never wrap
-- the fragments in COALESCE(..., FALSE) or otherwise choose a meaning for unknown inputs.
-- This evaluates the supplied model; it does not show that the model is a complete, legal,
-- or safe statement of a real-world rule.
--
-- Input columns (stable ID: name -> column):
-- v_b85aa55232f9: A1 -> "in_A1"
-- v_642166f389e0: B1 -> "in_B1"
-- v_022e27020ecc: A0 -> "in_A0"
-- v_83a0c82dd0b4: B0 -> "in_B0"
-- Output columns:
-- f_e0aba2c1efc2: equal -> "out_equal"
-- Assumptions (scope K; exported separately and never folded into an output):
-- none; every complete input row is in scope.
-- ----------------------------------------------------------------------------------------------
-- 1. Expression fragments (parenthesised; non-NULL boolean inputs required)
-- ----------------------------------------------------------------------------------------------
--
-- [out_equal] output equal (stable ID f_e0aba2c1efc2)
-- equal := XNOR(A1, B1) AND XNOR(A0, B0)
-- PRECONDITION: "in_A1", "in_B1", "in_A0", "in_B0" are non-NULL booleans.
-- (("in_A1" = "in_B1") AND ("in_A0" = "in_B0"))
--
-- ----------------------------------------------------------------------------------------------
-- 2. Guard template (read-only SELECT over an inputs list)
-- ----------------------------------------------------------------------------------------------
-- Replace the example rows between the markers with your own rows, or replace the inputs
-- CTE with a SELECT that provides the boolean columns listed in the header. status is
-- 'invalid_input' when any input is NULL, 'out_of_scope' when the assumptions are false, and
-- 'ok' otherwise; output columns are filled only for 'ok' rows (NULL elsewhere is an
-- envelope marker). Assumption columns are shown for rows with complete inputs.
WITH inputs ("row_id", "in_A1", "in_B1", "in_A0", "in_B0") AS (
-- tangibool:example-rows:begin
VALUES
(1, FALSE, FALSE, FALSE, FALSE),
(2, FALSE, FALSE, FALSE, TRUE),
(3, FALSE, FALSE, TRUE, FALSE),
(4, FALSE, FALSE, TRUE, TRUE),
(5, FALSE, TRUE, FALSE, FALSE),
(6, FALSE, TRUE, FALSE, TRUE),
(7, FALSE, TRUE, TRUE, FALSE),
(8, FALSE, TRUE, TRUE, TRUE),
(9, TRUE, FALSE, FALSE, FALSE),
(10, TRUE, FALSE, FALSE, TRUE),
(11, TRUE, FALSE, TRUE, FALSE),
(12, TRUE, FALSE, TRUE, TRUE),
(13, TRUE, TRUE, FALSE, FALSE),
(14, TRUE, TRUE, FALSE, TRUE),
(15, TRUE, TRUE, TRUE, FALSE),
(16, TRUE, TRUE, TRUE, TRUE),
(17, NULL::boolean, FALSE, FALSE, FALSE)
-- tangibool:example-rows:end
),
checked AS (
SELECT
inputs.*,
CASE
WHEN "in_A1" IS NULL OR "in_B1" IS NULL OR "in_A0" IS NULL OR "in_B0" IS NULL THEN 'invalid_input'
ELSE 'ok'
END AS "status"
FROM inputs
)
SELECT
"row_id",
"in_A1",
"in_B1",
"in_A0",
"in_B0",
"status",
CASE WHEN "status" = 'ok' THEN (("in_A1" = "in_B1") AND ("in_A0" = "in_B0")) END AS "out_equal"
FROM checked
ORDER BY "row_id";
SMT-LIB
; Tangibool SMT-LIB export (tangibool.smtlib/1) ; Profile: SMT-LIB 2.6 Boolean subset (QF_UF): Bool constants, define-fun, let, push/pop, assert, check-sat, echo. ; Tested with Z3 5.1.0 (z3-solver 5.2.0, WebAssembly build). ; Model: not stated ; Source revision: reference ; Interpretation status: not stated ; Exporter: 1.0.0 (engine 1.0.0; semantics tangibool-semantics/1) ; Logic digest: 80541868ec70b6db7650faa5f60a35cdc3317f7c52006b01250ed71dae57989c ; Assumptions digest: d58ee1ad38e23e5093e4baa1047b5ae70d6972e08f555e34ac3fa16df63c4a78 ; Mode: decision ; ; Reading results: each query block states what sat and unsat mean for its question. A sat ; answer comes with a witness or counterexample (ask for it with (get-model) after sat only); ; unsat settles that scoped query and is solver-checked, not an independently checked proof ; certificate; unknown settles nothing. Blocks are scoped with push/pop, so assertions never ; accumulate across questions. This checks the supplied model, not whether it is a complete, ; legal, or safe statement of a real-world rule. ; ; Symbols (stable ID: name -> symbol): ; v_b85aa55232f9: A1 -> in_A1 ; v_642166f389e0: B1 -> in_B1 ; v_022e27020ecc: A0 -> in_A0 ; v_83a0c82dd0b4: B0 -> in_B0 ; f_e0aba2c1efc2: equal -> out_equal (set-option :produce-models true) (set-info :smt-lib-version 2.6) (set-logic QF_UF) ; ---- Inputs (declared order) (declare-const in_A1 Bool) ; A1 (declare-const in_B1 Bool) ; B1 (declare-const in_A0 Bool) ; A0 (declare-const in_B0 Bool) ; B0 ; ---- Outputs (dependencies first) ; output equal (stable ID f_e0aba2c1efc2): XNOR(A1, B1) AND XNOR(A0, B0) (define-fun out_equal () Bool (and (= in_A1 in_B1) (= in_A0 in_B0))) ; ---- Assumptions (the scope K; never folded into an output) ; K: conjunction of the enabled, confirmed assumptions (true when there are none) (define-fun K () Bool true) ; ---- Definitions only: nothing is asserted and no check is run. ; Add (assert ...) and (check-sat) inside (push 1) ... (pop 1) to ask a question.
LaTeX
equal = \overline{\mathit{A1} \oplus \mathit{B1}} \cdot \overline{\mathit{A0} \oplus \mathit{B0}}El error habitual
Construir la igualdad con XOR en vez de XNOR y olvidar la inversión final. XOR(A1, B1) AND XOR(A0, B0) es verdadero cuando los dos bits difieren, no cuando coinciden; en la tabla enciende filas como A1 = FALSO, B1 = VERDADERO, A0 = FALSO, B0 = VERDADERO, donde los números son 0 y 3.
Preguntas
¿Por qué la FND tiene dieciséis literales y la FNC solo ocho?
La FNC es una conjunción de las dos pruebas XNOR, cada una un par de cláusulas de dos literales, así que no necesita multiplicación cruzada. La FND tiene que distribuir el AND sobre los dos XNOR y listar cada combinación de valores coincidentes, cuatro términos que nombran las cuatro entradas.
Relacionado
Operadores y compuertas
- Compuerta AND (puerta Y): tabla de verdad de 2, 3 y 4 entradas, símbolo y expresión
- Compuerta XNOR: tabla de verdad, símbolo y equivalencia con el bicondicional
Herramientas
- Generador de tablas de verdad: cualquier expresión booleana, hasta 12 variables, con columnas intermedias
- Calculadora y simplificador de álgebra de Boole paso a paso (cada ley nombrada y verificada)
- Solucionador de mapas de Karnaugh: de 2 a 4 variables, agrupaciones, SOP y POS
Véase también
- Comparador de un bit: A mayor que B
- XNOR construido con AND, OR y NOT
- Compuerta XNOR: tabla de verdad, símbolo y equivalencia con el bicondicional
- FNC frente a FND: qué forma normal para cada tarea
- Conversor a FNC y FND: formas normales conjuntiva y disyuntiva, mintérminos y maxtérminos
- Eliminación de XNOR: XNOR(A, B) = A ↔ B
Ejemplos resueltos
Generado a partir del motor de Tangibool, semántica tangibool-semantics/1, motor 1.0.0, compilación . Cada tabla, mapa, simplificación y veredicto de estas páginas lo calculó el motor de Tangibool al compilar el sitio, y cada afirmación la volvió a comprobar el mismo verificador exacto que usa la app. Los límites se indican donde aplican. © 2026 Foreranger LTD.