{"schema_version":"ocme-site-results-v1","locale":"en","page_type":"derivations","facts":{"questions":36000,"reviewed":36000,"display_candidates":0,"knowledge":302,"guides":299,"paths":59,"batches":360,"families":1441,"atlas":302,"core":80,"evidence":9,"formal_evidence":5,"formal_subjects":4,"lean_files":6,"lean_toolchain":"leanprover/lean4:v4.30.0","question_state":"candidate","english_state":"ai_candidate","question_Lean":"NOT_RUN","canonical_truth_promotion":false},"filters":{"q":"mko-inner-product-induced-norm"},"kind":"guides","total":1,"pages":1,"page":1,"entries":[{"id":"derivation-mko-inner-product-induced-norm-01","title":{"zh-Hant":"內積誘導範數：證明 √⟨x,x⟩ 是範數並在 ℝ² 正定矩陣下精確計算","en":"Inner-product-induced norm: proving √⟨x,x⟩ is a norm and computing exactly for a positive-definite matrix on ℝ²"},"summary":{"zh-Hant":"在任一實內積空間中證明 N(v)=√⟨v,v⟩ 是範數：非負與分離、絕對齊次、三角不等式（經由完整證明的 Cauchy–Schwarz）。再在 ℝ² 上以 A=[[2,1],[1,2]] 定義的內積，對 x=(1,0)、y=(0,1) 精確算出平方範數、距離平方，並做 Cauchy–Schwarz、三角不等式與平行四邊形恆等式的實例核對。","en":"In any real inner-product space, prove that N(v)=√⟨v,v⟩ is a norm: nonnegativity and separation, absolute homogeneity, and the triangle inequality (via a fully proved Cauchy–Schwarz inequality). Then, on ℝ² with the inner product given by A=[[2,1],[1,2]], compute exactly the squared norms and the squared distance for x=(1,0) and y=(0,1), and check Cauchy–Schwarz, the triangle inequality and the parallelogram identity on this instance."},"mko_ids":["mko-inner-product-induced-norm"]}],"title":"Concept derivation guides"}