"pseudonorm" meaning in All languages combined

{
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "pseudonorm (not comparable)",
      "name": "en-adj"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
  "senses": [
    {
      "categories": [
        {
          "kind": "other",
          "name": "English entries with incorrect language header",
          "parents": [
            "Entries with incorrect language header",
            "Entry maintenance"
          ],
          "source": "w"
        }
      ],
      "examples": [
        {
          "ref": "2016, Bijit Kumar Das, Mrityunjoy Chakraborty, “Adaptive Combination of l0 LMS Adaptive Filters for Sparse System Identification in Fluctuating Noise Power”, in arXiv",
          "text": "Recently, the l0-least mean square (l0-LMS) algorithm has been proposed to identify sparse linear systems by employing a sparsity-promoting continuous function as an approximation of l0 pseudonorm penalty.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "pseudonormal"
      ],
      "id": "en-pseudonorm-en-adj-DPn2uWsV",
      "links": [
        [
          "pseudonormal",
          "pseudonormal"
        ]
      ],
      "tags": [
        "not-comparable"
      ]
    }
  ],
  "word": "pseudonorm"
}

{
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "pseudonorm (not comparable)",
      "name": "en-adj"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
  "senses": [
    {
      "categories": [
        "English adjectives",
        "English entries with incorrect language header",
        "English lemmas",
        "English terms with quotations",
        "English uncomparable adjectives"
      ],
      "examples": [
        {
          "ref": "2016, Bijit Kumar Das, Mrityunjoy Chakraborty, “Adaptive Combination of l0 LMS Adaptive Filters for Sparse System Identification in Fluctuating Noise Power”, in arXiv",
          "text": "Recently, the l0-least mean square (l0-LMS) algorithm has been proposed to identify sparse linear systems by employing a sparsity-promoting continuous function as an approximation of l0 pseudonorm penalty.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "pseudonormal"
      ],
      "links": [
        [
          "pseudonormal",
          "pseudonormal"
        ]
      ],
      "tags": [
        "not-comparable"
      ]
    }
  ],
  "word": "pseudonorm"
}